20XX
M. Fabris, G. Michieletto, A. Cenedese.
A Proximal Point Approach for Distributed System State Estimation. IFAC World Congress (IFAC2020) - [accepted], 20XX
Abstract:
System state estimation constitutes a key problem in several applications involving
multi-agent system architectures. This rests upon the estimation of the state of each agent in
the group, which is supposed to access only relative measurements w.r.t. some neighbors state.
Exploiting the standard least-squares paradigm, the system state estimation task is faced in this
work by deriving a distributed Proximal Point-based iterative scheme. This solution entails the
emergence of interesting connections between the structural properties of the stochastic matrices
describing the system dynamics and the convergence behavior toward the optimal estimate. A
deep analysis of such relations is provided, jointly with a further discussion on the penalty
parameter that characterizes the Proximal Point approach.
[ abstract ] [
BibTeX]
G. Michieletto, N. Lissandrini, A. Antonello, R. Antonello, A. Cenedese.
Dual Quaternion Delay Compensating Maneuver Regulation for Fully Actuated UAVs. IFAC World Congress (IFAC2020) - [accepted], 20XX
Abstract:
In aerial robotics, path following constitutes a popular
task requiring a vehicle to pursue a given trajectory.
Resting upon the fulfillment of a desired time law,
trajectory tracking techniques often turn out to be
ineffective in presence of external disturbances, favoring
the adoption of maneuver regulation strategies wherein the
desired trajectory is parameterized in terms of the
path-variable. In this scenario, this work proposes a new
delay-compensating maneuver regulation controller for fully
actuated aerial vehicles, whose aim is to guarantee the
perfect tracking of a given path in the shortest time
interval. The innovative aspect of such a solution relies
on the introduction of a recovery term that compensates for
possible delays in
the task execution. In addition, the dual-quaternion
formalism is adopted to model the dynamics of the aerial
platforms allowing feedback linearize the whole system,
including both position and attitude, with a single
controller. The tests conducted in Gazebo physic simulator
show that the proposed controller outperforms the popular
trajectory tracking PID regulators.
[ abstract ] [
BibTeX]
A. Favrin, V. Nenchev, A. Cenedese.
Learning to falsify automated driving vehicles with prior knowledge. IFAC World Congress (IFAC2020) - [accepted], 20XX
Abstract:
While automated driving technology has achieved a tremendous progress, the
scalable and rigorous testing and verification of safe automated and autonomous driving vehicles
remain challenging. This paper proposes a learning-based falsification framework for testing the
implementation of an automated or self-driving function in simulation. We assume that the
function specification is associated with a violation metric on possible scenarios. Prior knowledge
is incorporated to limit the scenario parameter variance and in a model-based falsifier to guide
and improve the learning process. For an exemplary adaptive cruise controller, the presented
framework yields non-trivial falsifying scenarios with higher reward, compared to scenarios
obtained by purely learning-based or purely model-based falsification approaches.
[ abstract ] [
BibTeX]
A. Fabris, L. Parolini, S. Schneider, A. Cenedese.
Model-based approach to online map validation. IEEE Intelligent Vehicles (IV2020) - workshop on Online Map Validation and Road Model Creation - [accepted], 20XX
Abstract:
High-definition (HD) maps are one of the key
technologies supporting autonomous-driving vehicles (ADV).
Especially in urban scenarios, the field of view of sensors
is often limited, and HD map provides critical information
about upcoming road environmental data. Maps used for ADV
are high resolution with centimeter-level accuracy and their
correctness is fundamental when analyzing safety of upcoming
maneuvers.
This paper proposes an approach for online map validation
(OMV) based on spatial and temporal correlation of smart-
sensors. Smart sensors are capable of analyzing the validity of
regions of the map independently from one another. Results
from the sensors are then fused together over multiple regions
and time samples for providing a unified view to software
components deciding on upcoming maneuvers which areas of
the maps are consistent with sensor data and which not.
[ abstract ] [
BibTeX]
N. Lissandrini, A. Cenedese, A. Et.
NAPVIG: Online Reactive Navigation with On-Board Sensorsfor Unknown and Narrow Dynamic Environments. IEEE/RAS International Conference on Robotics and Automation (ICRA2021) - [submitted], 20XX [
BibTeX]
R. Fantinel, A. Cenedese.
[Undisclosed]. IEEE Transactions on Industrial Informatics [submitted], 20XX [
BibTeX]
G. Michieletto, A. Cenedese, D. Zelazo.
[Undisclosed]. IEEE Transactions on Control of Network Systems [provisionally accepted], 20XX [
BibTeX]
L. Varotto, A. Cenedese, A. Et.
[Undisclosed]. European Control Conference (ECC2021) [submitted], 20XX [
BibTeX]
R. Fantinel, A. Cenedese, A. Et.
[Undisclosed]. Conference on Computer Vision and Pattern Recognition (CVPR2021) - [submitted], 20XX [
BibTeX]
L. Varotto, A. Cenedese.
[Undisclosed]. Mediterranean Conference on Control and Automation (MED2021) [submitted], 20XX [
BibTeX]
G. Michieletto, A. Cenedese, A. Et.
[Undisclosed]. IEEE Transactions of Automation Science and Engineering [submitted], 20XX [
BibTeX]
2021
C. Favaretto, S. Spadone, C. Sestieri, V. Betti, A. Cenedese, S. Della Penna, M. Corbetta.
Multi-band MEG signatures of BOLD connectivity reorganization during visuospatial attention. Neuroimage, 2021
Abstract:
The functional architecture of the resting brain, as measured with the blood oxygenation level-dependent functional connectivity (BOLD-FC), is slightly modified during task performance. In previous work, we reported behaviorally relevant BOLD-FC modulations between visual and dorsal attention regions when subjects performed a visuospatial attention task as compared to central fixation (Spadone et al., 2015).
Here we use magnetoencephalography (MEG) in the same group of subjects to identify the electrophysiological correlates of the BOLD-FC modulation found in our previous work. While BOLD-FC topography, separately at rest and during visual attention, corresponded to neuromagnetic Band-Limited Power (BLP) correlation in the alpha and beta bands (8-30 Hz), BOLD-FC modulations evoked by performing the visual attention task (Spadone et al. 2015) did not match any specific oscillatory band BLP modulation. Conversely, following the application of an orthogonal spatial decomposition that identifies common inter-subject co-variations, we found that attention–rest BOLD-FC modulations were recapitulated by multi-spectral BLP-FC components. Notably, individual variability of alpha connectivity between Frontal Eye Fields and visual occipital regions, jointly with decreased interaction in the Visual network, correlated with visual discrimination accuracy. In summary, task-rest BOLD connectivity modulations match multi-spectral MEG BLP connectivity.
[ abstract ] [
url] [
BibTeX]
2020
A. Morato, S. Vitturi, F. Tramarin, A. Cenedese.
Assessment of Different OPC UA Implementations for Industrial IoT-based Measurement Applications. IEEE Transactions of Instrumentation and Measurements, (Early access), 2020
Abstract:
The Industrial IoT (IIoT) paradigm represents an attractive opportunity for new generation measurement applications, which are increasingly based on efficient and reliable communication systems to allow the extensive availability of continuous data from instruments and/or sensors, thus enabling real-time measurement analysis. Nevertheless, different communication systems and heterogeneous sensors and acquisition systems may be found in an IIoT-enabled measurement application, so that solutions need to be defined to tackle the issue of seamless, effective, and low-latency interoperability. A significant and appropriate solution is the Open Platform Communications (OPC) Unified Architecture (UA) protocol, thanks to its object–oriented structure that allows a complete contextualization of the information. The intrinsic complexity of OPC UA, however, imposes a meaningful performance assessment to evaluate its suitability in the aforementioned context. To this aim, this paper presents the design of a general yet accurate and reproducible measurement setup that will be exploited to assess the performance of the main open source implementations of OPC UA. The final goal of this work is to provide a characterization of the impact of this protocol stack in an IIoT-enabled Measurement System, in particular in terms of both the latency introduced in the measurement process and the power consumption.
[ abstract ] [
url] [
BibTeX]
N. Lissandrini, C.K. Verginis, P. Roque, A. Cenedese, D.V. Dimarogonas.
Decentralized Nonlinear MPC for Robust Cooperative Manipulation by Heterogeneous Aerial-Ground Robots. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS2020), pp. 1531--1536, 2020
Abstract:
Cooperative robotics is a trending topic nowadays
as it makes possible a number of tasks that cannot be performed
by individual robots, such as heavy payload transportation
and agile manipulation. In this work, we address the problem
of cooperative transportation by heterogeneous, manipulatorendowed robots. Specifically, we consider a generic number of
robotic agents simultaneously grasping an object, which is to be
transported to a prescribed set point while avoiding obstacles.
The procedure is based on a decentralized leader-follower
Model Predictive Control scheme, where a designated leader
agent is responsible for generating a trajectory compatible with
its dynamics, and the followers must compute a trajectory for
their own manipulators that aims at minimizing the internal
forces and torques that might be applied to the object by
the different grippers. The Model Predictive Control approach
appears to be well suited to solve such a problem, because
it provides both a control law and a technique to generate
trajectories, which can be shared among the agents. The
proposed algorithm is implemented using a system comprised
of a ground and an aerial robot, both in the robotic Gazebo
simulator as well as in experiments with real robots, where the
methodological approach is assessed and the controller design
is shown to be effective for the cooperative transportation task.
[ abstract ] [
url] [
BibTeX]
A. Morato, S. Vitturi, F. Tramarin, A. Cenedese.
Evaluation of Different OPC UA Industrial IoT solutions for Distributed Measurement Applications. International Instrumentation and Measurement technology Conference (I2MTC), 2020
Abstract:
The Industrial IoT scenario represents an interesting opportunity for distributed measurements systems, that are typically based on efficient and reliable communication systems, as well as the widespread availability of data from measurement instruments and/or sensors. The Open Platform Communications (OPC) Unified Architecture (UA) protocol is designed to ensure interoperability between heterogeneous sensors and acquisition systems, given its object-oriented structure allowing a complete contextualization of the information. Stemming from the intrinsic complexity of OPC UA, we designed an experimental measurement setup to carry out a meaningful performance assessment of its main open source implementations. The aim is to characterize the impact of the adoption of this protocol stack in a DMS in terms of both latency and power consumption, and to provide a general yet accurate and reproducible measurement setup.
[ abstract ] [
url] [
BibTeX]
G. Michieletto, A. Cenedese, L. Zaccarian, A. Franchi.
Hierarchical non-linear control for multi-rotor asymptotic stabilization based on zero-moment direction. Automatica, vol. 1172020
Abstract:
We consider the hovering control problem for a class of multi-rotor aerial platforms with generically oriented propellers. Given
the intrinsically coupled translational and rotational dynamics of such vehicles, we first discuss some assumptions for the
considered systems to reject moment disturbances and to balance the gravity force, which are translated into a geometric
characterization of the platforms that is usually fulfilled by both standard models and more general configurations. Hence,
we propose a control strategy based on the identification of a zero-moment direction for the applied force and the dynamic
state feedback linearization around this preferential direction, which allows to asymptotically stabilize the platform to a static
hovering condition. Stability and convergence properties of the control law are rigorously proved through Lyapunov-based
methods and reduction theorems for the stability of nested sets. Asymptotic zeroing of the error dynamics and convergence to
the static hovering condition are then confirmed by simulation results on a star-shaped hexarotor model with tilted propellers.
[ abstract ] [
url] [
BibTeX]
R. Antonello, F. Branz, F. Sansone, A. Cenedese, A. Francesconi.
High Precision Dual-Stage Pointing Mechanism for Miniature Satellite Laser Communication Terminals. IEEE Transactions on Industrial Electronics, 2020
Abstract:
This paper presents an innovative mechatronic design of a high-accuracy pointing mechanism for orbital laser communication terminals. The system is based on a dual-stage architecture and is miniaturized to fit nanosatellite-class spacecraft, aiming to enable optical communication on small-size space platforms. The focus is on control design aspects and on the performance assessment of an experimental prototype under emulated external environmental disturbances.
[ abstract ] [
url] [
BibTeX]
R. Fantinel, A. Cenedese.
Multistep hybrid learning: CNN driven by spatial–temporal features for faults detection on metallic surfaces. Journal of Electronic Imaging, vol. 4pp. 29, 2020
Abstract:
Solutions for the quality control of metallic surfaces are proposed. Specifically, we study a deflectometric apparatus based on coaxial structured light and the related algorithmic procedure, which is able to detect the faulty surface of a sample captured by a video sequence. First, by considering the metallic surface a dynamic scene illuminated under different light conditions, we develop the descriptor residuals of linear evolution of light (RLEL) that extracts the defectiveness information starting from the movement of the object without explicitly considering the physical characteristics of the light structure. Then, leveraging on RLEL, we present a hybrid learning (HL) technique capable of overcoming the data-driven approach used in classic deep learning (DL). By exploiting a multisteps training process, we combine the model-based descriptor RLEL and a classical data-driven convolutional neural network (CNN) to obtain an unconventional gray-box CNN, which exceeds the performance of popular DL solutions such as 3-D-inception and 3-D-residual DL networks. Remarkably, HL also shows its validity in comparing the performance of the same network structures trained not in a hybrid way, namely without the injection of the model-based information given by RLEL.
[ abstract ] [
url] [
BibTeX]
A. Colotti, A. Cenedese, S. Briot, I. Fantoni, A. Goldsztejn.
Stability Analysis and Reconfiguration Strategy for Multi-agent D-formation Control. 23rd CISM IFToMM Symposium on Robot Design, Dynamics and Control (ROMANSY2020), 2020
Abstract:
This paper introduces a new control approach to perform formation control tasks on multi-agent systems, called D-formation control. The D-formation controller is a gradient-descent control law that exploits a regularized potential function to efficiently achieve specific formations. Taking inspiration from the flocking of birds, this approach differentiates itself from the several formation control strategies that can be found in the literature thanks to its flexibility. In fact, the approach that is usually employed in formation control is to try to enforce a set of very strict constraints in order to achieve rigid, a priori defined structures. We will show that the D-formation approach greatly relaxes such conditions.
In this paper, the D-formation control problem is introduced, and the equilibrium configurations of the controller are characterized. Additionally, a strategy for switching from one stable equilibrium to another one, i.e. for changing the shape of the formation, is proposed.
[ abstract ] [
url] [
BibTeX]
2019
A. Masiero, F. Fissore, R. Antonello, A. Cenedese, A. Vettore.
A COMPARISON OF UWB AND MOTION CAPTURE UAV INDOOR POSITIONING. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XLII-2/W13, pp. 1695--1699, 2019
Abstract:
The number of applications involving unmanned aerial vehicles (UAVs) grew dramatically during the last decade. Despite such incredible success, the use of drones is still quite limited in GNSS denied environment: indeed, the availability of a reliable GNSS estimates of the drone position is still fundamental in order to enable most of the UAV applications. Given such motivations, in this paper an alternative positioning system for UAVs, based on low cost ultra-wideband band (UWB) is considered. More specifically, this work aims at assessing the positioning accuracy of UWB-based positioning thanks to the comparison with positions provided by a motion capture (MoCap) system. Since the MoCap accuracy is much higher than that of the UWB system, it can be safely used as a reference trajectory for the validation of UWB estimates. In the considered experiment the UWB system allowed to obtain a root mean square error of 39.4?cm in 3D positioning based on the use of an adaptive extended Kalman filter, where the measurement noise covariance was adaptively estimated.
[ abstract ] [
url] [
BibTeX]
Y. Chen, M. Bruschetta, R. Carli, A. Cenedese, D. Varagnolo, .. Et al.
A computationally efficient model predictive control scheme for space debris rendezvous. IFAC Symposium on Automatic Control in Aerospace (ACA 2019), 2019
Abstract:
We propose a non-linear model predictive scheme for planning fuel efficient maneuvers of small spacecrafts that shall rendezvous space debris. The paper addresses the specific issues of potential limited on-board computational capabilities and low-thrust actuators in the chasing spacecraft, and solves them by using a novel MatLab-based toolbox for real-time non-linear model predictive control (MPC) called MATMPC. This tool computes the MPC rendezvous maneuvering solution in a numerically efficient way, and this allows to greatly extend the prediction horizon length. This implies that the overall MPC scheme can compute solutions that account for the long time-scales that usually characterize the low-thrust rendezvous maneuvers. The so-developed controller is then tested in a realistic scenario that includes all the near-Earth environmental disturbances. We thus show, through numerical simulations, that this MPC method can successfully be used to perform a fuel-efficient rendezvous maneuver with an uncontrolled object, plus evaluate performance indexes such as mission duration, fuel consumption, and robustness against sensor and process noises.
[ abstract ] [
url] [
BibTeX]
A. Cenedese, L. Varotto.
A Distributed Approach to 3D Reconstruction in Marker Motion Capture Systems. International Conference on Distributed Smart Cameras (ICDSC 2019), 2019
Abstract:
Optical motion capture systems have attracted much interest over
the past years, due to their advantages with respect to non-optical
systems. Moreover, with the technological advances on camera
systems, computer graphics and computational methodologies, it
becomes technically and economically feasible to consider motion
capture systems made of large networks of cameras with embedded
communication and processing units on board (i.e., smart cameras).
Nevertheless, the approaches relying on the classical 3D recon-
struction methods would become inefficient in this case, since their
nature is intrinsically centralized. For this reason, we propose a dis-
tributed 3D reconstruction algorithm, which exploits a specific cam-
era nodes organization to efficiently process the information and
to remarkably speed up the scene reconstruction task. Indeed, nu-
merical simulations show that the proposed computational scheme
overcomes the principal state of the art solutions in terms of recon-
struction speed. Furthermore, the high processing speed does not
compromise the accuracy of the final result, since the algorithm is
designed to be robust to occlusions and measurement noise.
[ abstract ] [
url] [
BibTeX]
N. Bargellesi, M. Carletti, A. Cenedese, G.A. Susto, M. Terzi.
A Random Forest-based Approach for Hand Gesture Recognition with Wireless Wearable Motion Capture Sensors. 5th IFAC International Conference on Intelligent Control and Automation Sciences, 2019
Abstract:
Gesture Recognition has a prominent importance in smart environment and home automation. Thanks to the availability of Machine Learning approaches it is possible for users to define gestures that can be associated with commands for the smart environment. In this paper we propose a Random Forest-based approach for Gesture Recognition of hand movements starting from wireless wearable motion capture data. In the presented approach, we evaluate different feature extraction procedures to handle gestures and data with different duration. To enhance reproducibility of our results and to foster research in the Gesture Recognition area, we share the dataset that we have collected and exploited for the present work.
[ abstract ] [
url] [
BibTeX]
A. Cenedese, F. Tramarin, S. Vitturi, A. Et.
Comparative assessment of different OPC UA open–source stacks for embedded systems. IEEE Conference on Emerging Technologies and Factory Automation (ETFA2019), pp. 1127-1134, 2019
Abstract:
With the rise of Industry 4.0 and of the Industrial Internet, the computing and communication infrastructures achieved an essential role within process and factory automation, and cyberphysical systems in general. In this scenario, the OPC UA standard is currently becoming a widespread opportunity to enable interoperability among heterogeneous industrial systems. Nonetheless, OPC UA is characterized by a complex protocol architecture, that may impair the scalability of applications and may represent a bottleneck for its effective implementation in resource-constrained devices, such as low-cost industrial embedded systems. Several different OPC UA implementations are available, which in some significant cases are released under an open source license. In this context, the aim of this paper is to provide an assessment of the performance provided by some of these different OPC UA implementations, focusing specifically on potential development and resource bottlenecks. The analysis is carried out through an extensive experimental campaign explicitly targeting general purpose low-cost embedded systems. The final goal is to provide a comprehensive performance comparisons to allow devising some useful practical guidelines.
[ abstract ] [
url] [
BibTeX]
N. Lissandrini, G. Michieletto, R. Antonello, M. Galvan, A. Franco, A. Cenedese.
Cooperative Optimization of UAVs Formation Visual Tracking. Robotics, vol. 8(3), pp. 1--22 (Article Number 52), 2019
Abstract:
The use of unmanned vehicles to perform tiring, hazardous, repetitive tasks, is becoming a reality out of the academy laboratories, getting more and more interest for several application fields from the industrial, to the civil, to the military contexts. In particular, these technologies appear quite promising when they employ several low-cost resource-constrained vehicles leveraging their coordination to perform complex tasks with efficiency, flexibility, and adaptation that are superior to those of a single agent (even if more instrumented). In this work, we study one of said applications, namely the visual tracking of an evader (target) by means of a fleet of autonomous aerial vehicles, with the specific aim of focusing on the target so as to perform an accurate position estimation while concurrently allowing a wide coverage over the monitored area so as to limit the probability of losing the target itself. These clearly conflicting objectives call for an optimization approach that is here developed: by considering both aforementioned aspects and the cooperative capabilities of the fleet, the designed algorithm allows controling in real time the single fields of view so as to counteract evasion maneuvers and maximize an overall performance index. The proposed strategy is discussed and finally assessed through the realistic Gazebo-ROS simulation framework.
[ abstract ] [
url] [
BibTeX]
L. Varotto, M. Fabris, G. Michieletto, A. Cenedese.
Distributed Dual Quaternion Based Localization of Visual Sensor Networks. European Control Conference (ECC 2019), 2019
Abstract:
In this paper we consider the localization problem for a visual sensor network. Inspired by the alternate attitude and position distributed optimization framework discussed in [1], we propose an estimation scheme that exploits the unit dual quaternion algebra to describe the sensors pose. This representation is beneficial in the formulation of the optimization scheme allowing to solve the localization problem without designing two interlaced position and orientation estimators, thus improving the estimation error distribution over the two pose components and the overall localization performance. Furthermore, the numerical experimentation asserts the robustness of the proposed algorithm w.r.t. the initial conditions.
[ abstract ] [
url] [
BibTeX]
M. Fabris, A. Cenedese.
Distributed Strategies for Dynamic Coverage with Limited Sensing Capabilities. Mediterranean Conference on Control and Automation (MED19), 2019
Abstract:
In this work, it is presented the development of a novel distributed algorithm performing robotic coverage, clustering and dispatch around an event in static-obstacle-structured environments without relying on metric information. Specifically, the aim is to account for the trade-off between local communication given by bearing visibility sensors installed on each agent involved, optimal deployment in closed unknown scenarios and focus of a group of agents on one point of interest. The particular targets of this study can be summarized as 1. the minimization of the number of nodes and links maintaining a distributed approach over a connected communication graph; 2. the identification of an activation cluster around an event with a radial decreasing intensity, sensed by each agent; 3. the attempt to send the agents belonging to the cluster towards the most intense point in the scenario by minimizing a weighted isoperimetric functional.
[ abstract ] [
url] [
BibTeX]
G. Michieletto, A. Cenedese, A. Franchi.
Force-Moment Decoupling and Rotor-Failure Robustness for Star-Shaped Generically-Tilted Multi-Rotors. IEEE Conference on Decision and Control (CDC2019), pp. 2132--2137, 2019
Abstract:
Aerial robotics is increasingly becoming an attractive field of research thanks to the peculiar mixture of theoretical issues to be solved and technological challenges to be faced. In particular, recent developments have seen the multiplication of multi-rotor platforms that aim at improving the maneuverability of classical quadrotors in standard and harsh flying conditions, thus opening the field to comprehensive studies over the structural multi-rotor properties of actuation, decoupling, and robustness, which strongly depend on the mechanical configuration of the systems. This work collocates along this line of research by considering star-shaped generically-tilted multi-rotors (SGTMs), namely platforms with more than four possibly tilted propellers (along two tilting orthogonal axes). For these platforms, we investigate how the structural choices over the number of propellers and the tilting angles affect the force-moment decoupling features and, by recalling the robustness definition that refers to the hovering capabilities of the platform, we provide a robustness analysis and an hoverability assessment for SGTMs having five to eight actuators against the loss of one and two propellers.
[ abstract ] [
url] [
BibTeX]
G. Michieletto, A. Cenedese.
Formation Control for Fully Actuated Systems: a Quaternion-based Bearing Rigidity Approach. European Control Conference (ECC 2019), 2019
Abstract:
This work deals with formations of mobile agents with six independently controllable degrees of freedom able to retrieve relative bearing measurements w.r.t. some neighbors in the group. Exploiting the bearing rigidity framework, two control objectives are here addressed: ( i) the stabilization of these fully actuated multi-agent systems towards desired configurations, and (i i) their coordinated motion along directions guaranteeing the system shape maintenance. The proposed approach relies on a new formulation of the bearing rigidity theory based on the adoption of the unit quaternion formalism to describe the agents attitude. Through this representation choice, the formation dynamics is linear w.r.t. the input control velocities and the rigidity theory suggests the design of a distributed control scheme for both control goals whose efficacy is confirmed by numerical simulations.
[ abstract ] [
url] [
BibTeX]
A. Razman, A.S.A. Ghani, A. Cenedese, F.A. Adnan, G.A. Susto, K.M. Ismail, R.M. Musa, Y. Mukai, Z. Taha, A. Majeed.
Hunger Classification of Lates Calcarifer by means of an automated feeder and image processing. Computers and Electronics in Agriculture, vol. 1632019
Abstract:
In an automated demand feeder system, underlining the parameters that contribute to fish hunger is crucial in order to facilitate an optimised food allocation to the fish. The present investigation is carried out to classify the hunger state of Lates calcarifer. A video surveillance technique is employed for data collection. The video was taken throughout the daytime, and the fish were fed through an automated feeding system. It was demonstrated through this investigation that the use of such automated system does contribute towards a higher specific growth rate percentage of body weight as well as the total length by approximately 26.00% and 15.00%, respectively against the conventional time-based method. Sixteen features were feature engineered from the raw dataset into window sizes ranging from 0.5?min, 1.0?min, 1.5?min and 2.0?min, respectively coupled with the mean, maximum, minimum and variance for each of the distinctive temporal window sizes. In addition, the extracted features were analysed through Principal Component Analysis (PCA) for dimensionality reduction as well as PCA with varimax rotation. The data were then classified using a Support Vector Machine (SVM), k-Nearest Neighbor (k-NN) and Random Forest Tree models. It was demonstrated that the varimax based PCA yielded the highest classification accuracy with eight identified features. The prediction results based of the developed k-NN model on the selected features on the test data exhibited a classification rate of 96.5% was achieved suggesting that the features examined are non-trivial in classifying the fish hunger behaviour.
[ abstract ] [
url] [
BibTeX]
N. Trivellin, D. Barbisan, M. Pietrobon, D. Badocco, P. Pastore, A. Cenedese, G. Meneghesso, E. Zanoni, M. Meneghini.
Near-UV LED-based systems for low-cost and compact oxygen-sensing systems in gas and liquids. SPIE Conference - Photonics West Opto Proc. SPIE 10940, Light-Emitting Devices, Materials, and Applications, pp. 109400V, 2019
Abstract:
With this work we report on the design, development and testing of near UV LED-based systems for oxygen gas sensing. The design and developed system is an optoelectronic setup based on 405 nm LEDs which excites and measures the photoluminescence emitted from a porphyrin based luminophor. By means of an accurate optical and optoelectronic setup, the system is able to operate without the need of avalanche photodiodes, thus resulting in a compact and low energy structure. The optical setup is specifically designed to maximize both the LED light exciting the luminophor and converted light acquired from the sensor.
[ abstract ] [
url] [
BibTeX]
M. Fabris, G. Michieletto, A. Cenedese.
On the Distributed Estimation from Relative Measurements: a Graph-Based Convergence Analysis. European Control Conference (ECC 2019), 2019
Abstract:
The state estimation of a multi-agent system
resting upon noisy measurements constitutes a problem re-
lated to several applicative scenarios, such as, for example,
robotic localization and navigation, resource balancing and task
allocation, cooperative manipulation and coordinated control.
Adopting the standard least-squares approach, in this work
we derive both the (centralized) analytic solution to this issue
and two distributed iterative schemes, which allow to establish
a connection between the convergence behavior of consensus
algorithm towards the optimal estimate and the theory of the
stochastic matrices that describe the network system dynamics.
This study on the one hand highlights the role of the topological
links that define the neighborhood of agent nodes, while on the
other allows to optimize the convergence rate by easy parameter
tuning. The theoretical findings are validated considering dif-
ferent network topologies by means of numerical simulations.
[ abstract ] [
url] [
BibTeX]
M. Fabris, A. Cenedese, J. Hauser.
Optimal Time-Invariant Formation Tracking for a Second-Order Multi-Agent System. European Control Conference (ECC 2019), 2019
Abstract:
Given a multi-agent linear system, we formalize and solve a trajectory optimization problem that encapsulates trajectory tracking, distance-based formation control and input energy minimization. To this end, a numerical projection operator Newton's method is developed to find a solution by the minimization of a cost functional able to capture all these different tasks. To stabilize the formation, a particular potential function has been designed, allowing to obtain specified geometrical configurations while the barycenter position and velocity of the system follows a desired trajectory.
[ abstract ] [
url] [
BibTeX]
L. Varotto, A. Zampieri, A. Cenedese.
Street Sensor Set Selection through Map Segmentation and Observability Measures. Mediterranean Conference on Control and Automation (MED19), 2019
Abstract:
Nowadays, vehicle flow monitoring, model-based
traffic management, and congestion prediction are becoming
fundamental elements for the realization of the Smart City
paradigm. These tasks usually require wide sensor deploy-
ments, but, due to economical, practical, and environmental
constraints, they must be accomplished with a limited number
of sensors. Thus motivated, this work addresses the sensors
selection problem for urban street monitoring, by employing
a road map image as the basic information and considering
the placement of at most one sensor along each road with a
chosen number of available devices. To solve the problem, the
concept of system observability is exploited as the criterium for
optimal sensor placement, specifically related to the capability
of estimating the traffic flow in each road using the available
output measurements. In this framework, different integer non-
linear programming problems are proposed, whose solutions
are studied and analyzed by means of numerical simulations
on a real case scenario.
[ abstract ] [
url] [
BibTeX]
A. Morato, S. Vitturi, A. Cenedese, G. Fadel, F. Tramarin.
The Fail Safe over EtherCAT (FSoE) protocol implemented on the IEEE 802.11 WLAN. IEEE Conference on Emerging Technologies and Factory Automation (ETFA2019), pp. 1163-1170, 2019
Abstract:
Wireless networks are ever more deployed in industrial automation systems in various types of applications. A significant example in this context is represented by the transmission of safety data that, traditionally, was accomplished by wired systems. In this paper we propose an implementation of the Fail Safe over EtherCAT (FSoE) protocol on the top of IEEE 802.11 WLAN. The paper, after a general introduction of FSoE, focuses on the implementation of such protocol on commercial devices running UDP at the transport layer and connected via the IEEE 802.11 Wireless LAN. Then the paper presents some experimental setups and the tests that have been carried out on them. The obtained results are encouraging, since they show that good safety performance can be achieved even in the presence of wireless transmission media.
[ abstract ] [
url] [
BibTeX]
R. Fantinel, A. Cenedese.
Vision-based inspection system for metallic surfaces: CNN driven by features. Quality Control by Artificial Vision Conference (QCAV 2019) - Awarded for the "Most Innovative Application", 2019
Abstract:
We propose a novel approach for the inspection of metallic surfaces, integrable in the production phase. It consists of
a compact illumination and vision equipment that projects over a moving object a series of light bands. We developed a
specific feature extraction algorithms based on the dynamic evolution of the reflected light over the object surface, and we
built an Hybrid Learning System by feeding an Auto-Encoder CNN with this dynamic light features. The results obtained by
this novel approach reach higher performance respect classic Deep Learning networks and Machine Learning technique,
in critical light conditions too.
[ abstract ] [
url] [
BibTeX]
2018
A. Antonello, G. Michieletto, R. Antonello, A. Cenedese.
A Dual Quaternion Feedback Linearized Approach for Maneuver Regulation of Rigid Bodies. IEEE Control Systems Letters, vol. 2(3), pp. 327 -- 332, 2018
Abstract:
The adoption of the dual quaternion formalism to represent the pose (position and orientation) of a rigid body allows to design a single controller to regulate both its position and its attitude. In this work, we adopt such a pose representation to develop an exponentially stable maneuver regulation control law, ensuring robust path following in the presence of disturbances. The designed solution relies on the feedback linearized model of the dual quaternion based dynamics of the rigid body. Numerical results confirm the effectiveness of the proposed maneuver regulation approach when compared with trajectory tracking in a noisy scenario.
[ abstract ] [
url] [
BibTeX]
N. Normani, A. Urru, L. Abraham, M. Walsh, S. Tedesco, A. Cenedese, G.A. Susto, B. O'Flynn.
A Machine Learning Approach for Gesture Recognition with a Lensless Smart Sensor System. 15th International Conference on Wearable and Implantable Body Sensor Networks, pp. 136--139, 2018
Abstract:
Hand motion tracking traditionally re-
quires highly complex and expensive systems in terms
of energy and computational demands. A low-power,
low-cost system could lead to a revolution in this field
as it would not require complex hardware or additional
equipment. The present paper exploits the Multiple
Point Tracking algorithm developed at the Tyndall
National Institute as the basic algorithm to perform
a series of gesture recognition tasks. The hardware
relies upon the combination of a stereoscopic vision
of two novel Lensless Smart Sensors (LSS) combined
with IR filters and five hand-held LEDs to track. Track-
ing common gestures generates a six-gestures dataset,
which is then employed to train three Machine Learning
models: k-Nearest Neighbors, Support Vector Machine
and Random Forest. An offline analysis highlights how
different LEDs’ positions on the hand affect the clas-
sification accuracy. The comparison shows how the
Random Forest outperforms the other two models with
a classification accuracy of 90-91%.
[ abstract ] [
url] [
BibTeX]
S. Vitturi, A. Morato, A. Cenedese, G. Fadel, F. Tramarin, R. Fantinel.
An Innovative Algorithmic Safety Strategy for Networked Electrical Drive Systems. 16th International Conference on Industrial Informatics (INDIN18), pp. 368--373, 2018
Abstract:
In this paper we address the safety strategies for networked electrical drive systems, in the context of industrial automation. Specifically, it is considered the handling of errors and faults that may occur during the execution of safety related functions, on a set of electrical drives. Such devices, which operate in a coordinated way, are connected via an industrial communication network and use a safety industrial protocol. In this respect, a novel approach that exploits a distributed consensus algorithm to identify and possibly recover the aforementioned errors is devised and discussed in comparison with a traditional safe shut-down strategy. The theoretical performance figures and the effectiveness of the proposed approach are evaluated in a real industrial case study considering two different widespread network topologies.
[ abstract ] [
url] [
BibTeX]
F. Chiariotti, C. Pielli, A. Cenedese, A. Zanella, M. Zorzi.
Bike Sharing as a Key Smart City Service: State of the Art and Future Developments. 7th International Conference on Modern Circuits and Systems Technologies (MOCAST 2018), pp. 1--6, 2018
Abstract:
Bike-sharing has outgrown its first failures in the
’60s and ’70s and become ubiquitous around the world. This
rapid growth is strongly intertwined with the rise of Smart Cities:
the use of connected bikes makes the service more practical for
users, avoids thefts and provides a large amount of data for
system planners. Over the past few years, the research on bike-
sharing has bloomed, providing several innovative solutions to
improve the service and encourage citizens to use environmentally
friendly modes of transportation, reducing both traffic and
commuting times. In this work, we present the most promising
developments towards a tighter integration between Smart City
data and techniques and the operation and planning of bike-
sharing system, focusing on two model use-cases: New York City’s
CitiBike service, a large system with hundreds of stations, and
Padova’s GoodBike system, which has just 28 stations.
[ abstract ] [
url] [
BibTeX]
G. Michieletto, S. Milani, A. Cenedese, G. Baggio.
Improving Consensus-based Distributed Camera Calibration via Edge Pruning and Graph Traversal Initialization. Proceedings of the 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3166--3170, 2018
Abstract:
Over the past few years, a huge number of distributed camera calibration strategies have been proposed for video surveillance and monitoring systems involving mobile terminals. Many of the proposed solutions rely on consensus-based algorithms, which aim at estimating the configuration of the network via a message passing protocol. In this paper we propose an improved consensus-based distributed camera calibration strategy that exploits a robust initialization, together with a pruning protocol to remove faulty links which could propagate excessively-noisy information through the network reducing the convergence time. The proposed solution seems to improve the state-of-the-art strategies in terms of accuracy, convergence speed, and computational complexity.
[ abstract ] [
url] [
BibTeX]
F. Branz, M. Duzzi, L. Olivieri, F. Sansone, G. Michieletto, R. Antonello, A. Cenedese, A. Francesconi.
Laboratory validation of close navigation, rendezvous and docking technologies for nanosats. Proceedings of the 4S Symposium, 2018
Abstract:
Over the last decades, small satellites have
become very appealing among the space community for their low complexity and
high flexibility. Many proposed mission concepts foresee the employment of
miniature spacecraft for a variety of applications, many of which are
economically unfeasible with traditional vehicles. This is due to the fact that
the development of miniaturized and standardized space vehicles may
considerably reduce the design, manufacturing and lunch costs involved. Furthermore,
the reduced unitary mass of small satellites allows launches of multiple
vehicles equipped with independent functionalities, thus achieving increased
flexibility and redundancy. In the future, one additional opportunity could be
given by the capability to assemble spacecraft in orbit to form reconfigurable
structures. This would further boost the number of possibilities in terms of
applications and operations. Nevertheless, the novelty of such concept and the
intrinsic complexity of its practical realization still require a considerable
research effort. In fact, only few navigation and docking technologies for nano- and micro satellites
have been designed and proved in relevant environment. In this framework, the
authors focus on the development and validation of critical technologies for
close navigation, rendezvous and docking suitable for nanosatellites.
This
paper presents a laboratory experiment for the validation on a complete rendezvous,
navigation and docking package compatible with the common CubeSat standard. The
experiment is conducted on a low friction table, with one free moving vehicle
(chaser) that approaches and docks to a fixed target interface. The test
facility allows three degrees of freedom to the nanosat mock-up. The vehicle is
equipped with an autonomous package that features (1) a camera-based vision
system for relative navigation, (2) a set of independent electro-magnetic coils
for final alignment and soft docking, (3) a single-actuator hard docking system
for structural connection between the chaser and the target, (4) a dedicated
electronics package for motion control and system status monitoring. The mobile
platform is also equipped with a set of flat air bearing with a dedicated
high-pressure pneumatic circuit for frictionless in-plane motion.
This paper
describes the docking package, the CubeSat mock-up and the test facility in
details, with reference to the main design considerations. Numerical
simulations have been conducted to foresee the dynamical behaviour of the
system and to select the appropriate control algorithm. An intensive
experimental campaign aims at the validation of numerical results and at the
functional verification and performance estimation for each subsystem and for
the system as a whole. The numerical and experimental results are presented and
compared, allowing to draw useful conclusions for the future development steps.
[ abstract ] [
BibTeX]
A. Antonello, G. Michieletto, R. Antonello, A. Cenedese.
Maneuver Regulation vs. Trajectory Tracking for Fully Actuated UAVs: A Dual Quaternion Approach. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS2018), pp. poster 02/10 #13, 2018
Abstract:
Maneuver regulation emerges as an optimal strategy to perform robust path following in presence of disturbances, exploiting vehicle controllability and improving performances w.r.t. trajectory tracking. In this work we consider
maneuver regulation for a fully-actuated aerial platform in a
dual quaternion framework, which yields the additional benefit
of addressing the attitude and position control problem with
a single state controller. To this aim, the nonlinear dynamics
is first derived in a dual quaternion setup and then feedback
linearized to enable the design of a stable maneuver regulator.
This controller is compared with a standard PD scheme, w.r.t.
the capability of following a desired trajectory, and is then
further improved through the definition of a strategy to compensate for the cumulative delay due to external disturbances.
[ abstract ] [
url] [
BibTeX]
A. Cenedese, P. Bettini, M. Bonotto.
Model-based approach for magnetic reconstruction in axisymmetric nuclear fusion machines. IEEE Transactions on Plasma Science, vol. 46(3), pp. 636 - 644, 2018
Abstract:
This paper describes an approach for the magnetic
reconstruction in large scale tokamak devices that is suitable for a
real time employment in order to provide reference for an active
control action during the whole plasma evolution. This problem
can be seen as a free boundary problem, where the shape features
of the plasma are determined by the equilibrium with the external
sources, namely the active circuit currents and the eddy currents
flowing in the passive structures. In this respect, a dynamic model
is needed in order to estimate the induced currents and provide
a consistent representation of the whole system behavior during
the entire plasma discharge. Such a model is then coupled with
an iterative optimization procedure to provide a model of the
plasma that, superimposed with the external sources, minimizes
the error of the reconstructed magnetic map with reference to the
available sensor measurements. The analysis and the validation of
this approach are presented, resulting in a procedure that appears
to accurately follow the behavior of the system both during slow
varying evolution and during strongly dynamic events.
[ abstract ] [
url] [
BibTeX]
C. Favaretto, A. Cenedese.
Non-linear modeling and control of Mitochondrial Dynamics. 57th IEEE Conference on Decision and Control (CDC 2018), pp. 3491--3496, 2018
Abstract:
Mitochondrial Dynamics (MD) has recently
emerged as one of the most interesting topics in biology since
the intricate connection between energy production and MD
regulates cells development and function. On the other hand,
the impairment of such mechanism is strictly related to the
emergence of various diseases, among which neurodegenerative
disorders. In this work, we provide a simple, yet complete, and
well-posed mathematical model to describe the MD and the
related phenomena through a population-dynamics approach,
together with the ATP-energy turnover, which is an important
step to unravel the underlying dynamics of the whole cell system
and has a key role in its quality control. With the tools of
system theory, we highlight the positiveness of the system and
the presence of non-zero equilibria and compute bounds for
the involved system state quantities. Furthermore, we consider
a situation of impairment in the MD and design a control law,
based on input-output linearization and state-feedback control
able to allow a damaged system to compensate for the defect and
behave as a nominal one. In this scenario, we test two different
protocols that could be suggestive for treatment strategies.
[ abstract ] [
url] [
BibTeX]
M. Duzzi, M. Mazzucato, R. Casagrande, L. Moro, F. Trevisi, R. Vitellino, M. Vitturi, A. Cenedese, E.C. Lorenzini, A. Francesconi.
PACMAN experiment: a CubeSat-size integrated system for proximity navigation and soft-docking. Proceedings of the 4S Symposium, 2018
Abstract:
In the last years, international space-related
companies and agencies are manifesting great interest in on-orbit servicing.
Innovative solutions to perform on-orbit operations such as refuelling, payload
updating and maintenance, subsystems repairing and inspection are under study
and all the new ideas and technologies under development are perceived as
extremely functional and cost-effective, capable of increasing the operational
lifetime of a satellite and decreasing the costs related to its complete
replacement.
For these reasons, the development of an automatic,
standard and reliable docking system would simplify the accomplishment of
on-orbit servicing procedures. Presently, there has been an increasing interest
in developing different technologies for proximity navigation and rendezvous
manoeuvres but no competitive or commercial technologies are currently
available to perform autonomous rendezvous and docking between small-satellites.
One
promising solution is represented by relative magnetic navigation, where
the chaser relative position and attitude can be controlled thanks to magnetic
interactions with the target vehicle.
This
paper presents an overview of the PACMAN experiment:
PACMAN is a technology demonstrator developed by a team of university and PhD
students in the framework of ESA
Education Fly Your Thesis! 2017 programme and supported by the
University of Padova. The experiment has been selected
for the 68th ESA Parabolic Flight
Campaign that took place in December 2017. The main goal of the
project was to develop and validate in low-gravity conditions an integrated
system for proximity navigation and soft-docking based on magnetic
interactions, suitable for small-scale spacecraft. This has been accomplished
by launching a miniature spacecraft mock-up (1U CubeSat) towards a
free-floating target that generates a static magnetic field; a set of
actively-controlled magnetic coils on-board the spacecraft mock-up, assisted by
dedicated localization sensors, have been used to control its attitude and
position relative to the target. This experimental setup allowed to
study the behaviour of a miniature spacecraft subjected to controlled magnetic
interactions in low-gravity conditions and to validate the theoretical/numerical
models that describe such interactions.
The
paper describes the experiment design, realization and execution, from the initial
concept to the Parabolic Flight Campaign tests. The experiment working
principle is illustrated with particular attention towards the navigation and soft-docking
subsystems, and the analysis of retrieved scientific results is finally presented.
[ abstract ] [
BibTeX]
M. Duzzi, M. Mazzucato, R. Casagrande, L. Moro, F. Trevisi, R. Vitellino, M. Vitturi, A. Cenedese, E.C. Lorenzini, A. Francesconi.
PACMAN experiment: a Parabolic Flight Campaign student experience. Proceedings of the 2nd Symposium on Space Educational Activities, 2018
Abstract:
Presently, no competitive or commercial solution is
currently available to perform autonomous rendezvous and docking between
small-satellites. Therefore, in the last years there has been an increasing
interest in developing different technologies for proximity navigation and
rendezvous manoeuvres, addressing the main issues of fuel consumption and the
strong impact of close range navigation subsystems on satellites mass budget
and complexity. One promising solution is represented by relative magnetic
navigation, where the chaser relative position and attitude can be controlled
thanks to magnetic interactions with the target vehicle.
PACMAN experiment is a technology demonstrator that has been developed by
a team of university and PhDs students in the framework of ESA Education Fly Your Thesis! 2017
programme and supported by the University of Padova. The experiment has been selected to fly during the 68th ESA Parabolic Flight Campaign, currently scheduled to
take place this December. The main goal of the project is to
develop and validate in low-gravity conditions an integrated system for
proximity navigation and soft-docking based on magnetic interactions, suitable
for small-scale spacecraft. This will be accomplished by launching a miniature
spacecraft mock-up towards a free-floating target that generates a static
magnetic field; a set of actively-controlled magnetic coils on-board the
spacecraft mock-up, assisted by dedicated localization sensors, will be used to
control its attitude and position relative to the target.
The realization of PACMAN experiment will
allow to study the behaviour of a miniature spacecraft subjected to controlled
magnetic interactions in low-gravity conditions and to validate the
theoretical/numerical models that describe such interactions.
This
paper presents an overview from the concept and design of the experiment to the
Parabolic Flight Campaign tests. The experiment working principle will be
illustrated, along with the design and assembly phases. Particular attention
will be made towards the problem solving approach. Alternatives and backup
solutions are introduced as part of the lessons learned during the entire
programme. Finally, the analysis of retrieved scientific results will be
showed.
[ abstract ] [
url] [
BibTeX]
C. Favaretto, S. Spadone, S. Della Penna, A. Cenedese, M. Corbetta.
Spatio-temporal relationships between BOLD and MEG signals at rest or during visuospatial attention. in Organization for Human Brain Mapping (OHBM) Annual Meeting, pp. poster #1910, 2018
Abstract:
The relationship between fMRI and MEG signals between different cortical regions (functional connectivity, FC) has been extensively analyzed in the resting state (De Pasquale et al 2010; Brookes et al 2011; Hipp et al 2012). Much less is known about FC modulations from rest to task states, and how they appear respectively in these two imaging modalities. Previously we have shown task-specific alterations of FC in fMRI during a visuospatial attention task (Spadone et al., PNAS, 2015). Specifically, decrements of resting correlation in visual areas were coupled with increments of correlation between visual and dorsal attention regions. Here, we compared fMRI with band-limited power (BLP) correlation obtained with MEG on the same group of subjects. Aim (i) is to measure frequency specific task-related FC modulations in MEG. Aim (ii) is to compare fMRI- and MEG-FC modulations (task-rest).
[ abstract ] [
url] [
BibTeX]
N. Trivellin, D. Barbisan, D. Badocco, P. Pastore, G. Meneghesso, M. Meneghini, E. Zanoni, G. Belgioioso, A. Cenedese.
Study and development of a fluorescence based sensor system for monitoring oxygen in wine production: The WOW project. Sensors, vol. 18(4), pp. 1130, 2018
Abstract:
The importance of oxygen in the winemaking process is widely known, as it affects the chemical aspects and therefore the organoleptic characteristics of the final product. Hence, it is evident the usefulness of a continuous and real-time measurements of the levels of oxygen in the various stages of the winemaking process, both for monitoring and for control. The WOW project has focused on the design and the development of an innovative device for monitoring the oxygen levels in wine. This system is based on the use of an optical fiber to measure the luminescent lifetime variation of a reference metal/porphyrin complex, which decays in presence of oxygen. The developed technology results in a high sensitivity and low cost sensor head that can be employed for measuring the dissolved oxygen levels at several points inside a wine fermentation or aging tank. This system can be complemented with dynamic modeling techniques to provide predictive behavior of the nutrient evolution in space and time given few sampled measuring points for both process monitoring and control purposes. The experimental validation of the technology has been first performed in a controlled laboratory setup to attain calibration and study sensitivity with respect to different photo-luminescent compounds and alcoholic or non-alcoholic solutions, and then in an actual case study during a measurement campaign at a renown Italian winery.
[ abstract ] [
url] [
pdf] [
BibTeX]
G. Marchiori, A. Cenedese, .. Et al.
Study of a Plasma Boundary Reconstruction Method based on Reflectometric Measurements for Control Purposes. IEEE Transactions on Plasma Science, vol. 46(5), pp. 1285--1290, 2018
Abstract:
A purely geometric approach has been investigated to reconstruct the Demonstration Fusion Power Reactor (DEMO) plasma boundary for control purposes. The whole plasma boundary is reconstructed by using a deformable template method based on B-splines. The final curve shape is achieved by minimizing the distance between a limited number of estimated and measured (at present provided by an equilibrium code) plasma boundary points along the reflectometer lines of sight. The resulting unconstrained optimization problem is solved by a simulated annealing algorithm. The method is complemented by including the available plasma and poloidal field coil current measurements to refine the boundary reconstruction in the X-point region. The robustness with respect to random measurement random errors and to a reduction in the number of measurements is discussed. The main equilibrium and shape geometric quantities (such as plasma cross-sectional area, plasma center position, elongation, and triangularity) were computed and compared to the corresponding quantities of a DEMO reference equilibrium.
[ abstract ] [
url] [
BibTeX]
2017
S. Borile, A. Pandharipande, D. Caicedo, L. Schenato, A. Cenedese.
A data-driven daylight estimation approach to lighting control. IEEE Access, vol. 5pp. pp. 21461-21471, 2017
Abstract:
We consider the problem of controlling a smart lighting system of multiple luminaires with collocated occupancy and light sensors. The objective is to attain illumination levels higher than specified values (possibly changing over time) at the workplace by adapting dimming levels using sensor information, while minimizing energy consumption. We propose to estimate the daylight illuminance levels at the workplace based on the daylight illuminance measurements at the ceiling. More specifically, this daylight estimator is based on a model built from data collected by light sensors placed at workplace reference points and at the luminaires in a training phase. Three estimation methods are considered: Regularized least squares, locally weighted regularized least squares, and cluster-based regularized least squares. This model is then used in the operational phase by the lighting controller to compute dimming levels by solving a linear programming problem, in which power consumption is minimized under the constraint that the estimated illuminance is higher than a specified target value. The performance of the proposed approach with the three estimation methods is evaluated using an open-office lighting model with different daylight conditions. We show that the proposed approach offers reduced under-illumination and energy consumption in comparison to existing alternative approaches.
[ abstract ] [
url] [
BibTeX]
M. Terzi, A. Cenedese, G.A. Susto.
A multivariate symbolic approach to activity recognition for wearable applications. IFAC World Congress 2017, pp. 16435-16440, 2017
Abstract:
With the aim of monitoring human activities (in critical tasks as well as in leisure and
sport activities), wearable devices provide enhanced usability and seamless human experience
with respect to other portable devices (e.g. smartphones). At the same time, though, wearable
devices are more resource-constrained in terms of computational capability and memory, which
calls for the design of algorithmic solutions that explicitly take into account these issues. In
this paper, a symbolic approach for activity recognition with wearable devices is presented:
the Symbolic Aggregate approXimation technique is here extended to multi-dimensional time
series, in order to capture the mutual information of different dimensions. Moreover, a novel
approach to identify gestures within activities is here presented. The performance of the
proposed methodology is tested on the two heterogeneous datasets related to cross-country
skiing and daily activities.
[ abstract ] [
pdf] [
BibTeX]
A. Cenedese, F. Tramarin, S. Vitturi.
An Energy Efficient Ethernet Strategy Based on Traffic Prediction and Shaping. IEEE Transactions on Communications, vol. 65(1), pp. 270-282, 2017
Abstract:
Recently, different communities in computer science, telecommunication and control systems have devoted a huge effort towards the design of energy efficient solutions for data transmission and network management. This paper collocates along this research line and presents a novel energy efficient strategy conceived for Ethernet networks. The proposed strategy combines the statistical properties of the network traffic with the opportunities offered by the IEEE 802.3az amendment to the Ethernet standard, called Energy Efficient Ethernet (EEE). This strategy exploits the possibility of predicting the incoming traffic from the analysis of the current data flow, which typically presents a self-similar behavior. Based on the prediction, Ethernet links can then be put in a low power consumption state for the intervals of time in which traffic is expected to be of low intensity. Theoretical bounds are derived that detail how the performance figures depend on the parameters of the designed strategy and scale with respect to the traffic load. Furthermore, simulations results, based on both real and synthetic traffic traces, are presented to prove the effectiveness of the strategy, which leads to considerable energy savings at the cost of only a limited bounded delay in data delivery.
[ abstract ] [
url] [
pdf] [
BibTeX]
N. Bof, R. Carli, A. Cenedese, L. Schenato.
Asynchronous Distributed Camera Network Patrolling under Unreliable Communication. IEEE Transactions on Automatic Control, vol. 62(11)pp. 5982-5989, 2017
Abstract:
In this paper, we study the problem of real-time optimal distributed partitioning for perimeter patrolling in the context of multicamera networks for surveillance, where each camera has limited mobility range and speed, and the communication is unreliable. The objective is to coordinate the cameras in order to minimize the time elapsed between two different visits of each point of the perimeter. We address this problem by casting it into a convex problem in which the perimeter is partitioned into nonoverlapping segments, each patrolled by a camera that sweeps back and forth at the maximum speed. We then propose an asynchronous distributed algorithm that guarantees that these segments cover the whole patrolling perimeter at any time and asymptotically converge to the optimal centralized solution under reliable communication. We finally modify the proposed algorithm in order to attain the same convergence and covering properties even in the more challenging scenario, where communication is lossy and there is no channel feedback, i.e., the transmitting camera is not aware whether a packet has been received or not by its neighbors.
[ abstract ] [
url] [
pdf] [
BibTeX]
C. Favaretto, D.S. Bassett, A. Cenedese, F. Pasqualetti.
Bode meets Kuramoto: Synchronized Clusters in Oscillatory Networks. 2017 American Control Conference (ACC17), pp. 2799--2804, 2017
Abstract:
In this paper we study cluster synchronization in
a network of Kuramoto oscillators, where groups of oscillators
evolve cohesively and at different frequencies from the neighboring
oscillators. Synchronization is critical in a variety of
systems, where it enables complex functionalities and behaviors.
Synchronization over networks depends on the oscillators’
dynamics, the interaction topology, and coupling strengths, and
the relationship between these different factors can be quite
intricate. In this work we formally show that three network
properties enable the emergence of cluster synchronization.
Specifically, weak inter-cluster connections, strong intra-cluster
connections, and sufficiently diverse natural frequencies among
oscillators belonging to different groups. Our approach relies on
system-theoretic tools, and is validated with numerical studies.
[ abstract ] [
url] [
pdf] [
BibTeX]
C. Favaretto, A. Cenedese, F. Pasqualetti.
Cluster Synchronization in Networks of Kuramoto Oscillators. IFAC 2017 World Congress, pp. 2485--2490, 2017
Abstract:
A broad class of natural and man-made systems exhibits rich patterns of clustersynchronization in healthy and diseased states, where different groups of interconnectedoscillators converge to cohesive yet distinct behaviors. To provide a rigorous characterizationof cluster synchronization, we study networks of heterogeneous Kuramoto oscillators and wequantify how the intrinsic features of the oscillators and their interconnection paramentersaffect the formation and the stability of clustered configurations. Our analysis shows that clustersynchronization depends on a graded combination of strong intra-cluster and weak inter-clusterconnections, similarity of the natural frequencies of the oscillators within each cluster, andheterogeneity of the natural frequencies of coupled oscillators belonging to different groups. Theanalysis leverages linear and nonlinear controltheoretic tools, and it is numerically validated.
[ abstract ] [
pdf] [
BibTeX]
F. Carbone, A. Cenedese, C. Pizzi.
Consensus-based Anomaly Detection for Efficient Heating Management. IEEE International Conference on Smart City Innovations (IEEE SCI 2017), pp. 1284--1290, 2017
Abstract:
The analysis of data to monitor human-related
activities plays a crucial role in the development of smart policies
to improve well being and sustainability of our cities. For several
applications in this context anomalies in time series can be
associated to smaller timeframes such as days or weeks.
In this work we propose a consensus-based anomaly detection
approach that exploits the power of the Symbolic Aggregate
approXimation (SAX) and the specificity of such time series.
In our approach, the normalization of the signal becomes a
proper element of the modeling. In fact, we conjecture that
different normalization horizons allow to include in the shape
of the timeseries patterns an additional, variable, component
from a longer period trend. To support the analysis phase, a
calendar can be used as an additional source of information to
discriminate between really unwanted anomalies and expected
anomalies (e.g. weekends), or even to signal a possible anomaly
whenever a “normal” behavior is not expected.
Preliminary experiments on temperature analysis in an indoor
environment, with the scope of thermal energy saving, showed
that our approch effectivly identified of all known anomalies, and
also pointed out some unexpected, but clear, anomalies.
[ abstract ] [
url] [
pdf] [
BibTeX]
A. Cenedese, M. Luvisotto, G. Michieletto.
Distributed Clustering Strategies in Industrial Wireless Sensor Networks. IEEE Transactions on Industrial Informatics, vol. 13(1), pp. 228-237, 2017
Abstract:
Wireless sensor networks (WSNs) can provide numerous benefits in industrial automation. By removing the cable infrastructure, the wireless architecture enables the possibility for nodes in a network to dynamically and autonomously group into clusters according to the communication features and the data they collect. This capability allows to leverage the flexibility and robustness of industrial WSNs in supervisory intelligent systems for high-level tasks, such as, for example, environmental sensing, condition monitoring, and process automation. In this paper, a clustering strategy is studied that partitions a sensor network into a nonfixed number of nonoverlapping clusters according to the communication network topology and measurements distribution: To this aim, both a centralized and a distributed algorithm are designed that do not require a cluster-head structure or other network assumptions. As a validation, these strategies are tested on a real dataset coming from a structured environment and the effectiveness of the clustering procedure is also investigated to perform anomalies detection in an industrial production process.
[ abstract ] [
url] [
pdf] [
BibTeX]
F. Boem, R. Reci, A. Cenedese, T. Parisini.
Distributed Clustering-based Sensor Fault Diagnosis for HVAC Systems. IFAC World Congress 2017, pp. 4281--4286, 2017
Abstract:
The paper presents a distributed Sensor Fault Diagnosis architecture for Industrial
Wireless Sensor Networks monitoring HVAC systems, by exploiting a recently proposed
distributed clustering method. The approach allows the detection and isolation of multiple
sensor faults and considers the possible presence of modeling uncertainties and disturbances.
Detectability and isolability conditions are provided. Simulation results show the effectiveness
of the proposed method for an HVAC system.
[ abstract ] [
pdf] [
BibTeX]
M. Duzzi, A. Francesconi, A. Cenedese, .. Et al.
Electromagnetic position and attitude control for PACMAN experiment. Guidance, Navigation and Control 2017: 10th ESA GNC Conference, 2017
Abstract:
In-space proximity manoeuvres between small satellites would enable a wide number of oper-
ations, among all docking and assembly of large modular structures. Electromagnetic interac-
tions are the simplest solution employed for proximity operations with respect to fuel-based solu-
tions that strongly influence spacecraft operational life. Preliminary studies have been performed
mostly on low-friction and low-gravity facilities and in-space demonstrations have been only re-
cently financed.
In this framework, PACMAN (Position and Attitude Control with MAgnetic Navigation) exper-
iment represents a technology demonstrator whose main goal is to develop and validate in low-
gravity conditions an integrated and innovative system for proximity navigation and soft docking
based on magnetic interactions. The project has been selected to fly during the 68th ESA Parabolic
Flight Campaign within ESA Education Fly Your Thesis! 2017 Programme.
The idea of PACMAN is to actively exploit magnetic interactions for relative position and attitude
control during rendezvous and proximity operations between small-scale spacecraft. This will be
accomplished by launching a 1U CubeSat mock-up towards a free floating-target that generates an
electromagnetic field; a set of actively-controlled magnetic coils on-board the CubeSat, assisted
by dedicated localization sensors, will be used to control its attitude and position relative to the
target.
This paper will focus on the Guidance, Navigation and Control subsystem of the experiment and
the tests performed at components level.
[ abstract ] [
BibTeX]
M. Bonotto, A. Cenedese, P. Bettini.
Krylov Subspace Methods for Model Order Reduction in Computational Electromagnetics. IFAC 2017 World Congress, pp. 6529--6534, 2017
Abstract:
This paper presents a model order reduction method via Krylov subspace projection,
for applications in the field of computational electromagnetics (CEM). The approach results
to be suitable both for SISO and MIMO systems, and is based on the numerically robust
Arnoldi procedure. We have studied the model order reduction as the number of inputs and
outputs changes, to better understand the behavior of the reduction technique. Relevant CEM
examples related to the reduction of finite element method models are presented to validate this
methodology, both in the 2D and in the 3D case.
[ abstract ] [
pdf] [
BibTeX]
M. Bonotto, A. Cenedese, P. Bettini.
Model order reduction of large-scale state-space models in fusion machines via Krylov methods. IEEE Transactions on Magnetics, vol. 53(6), pp. 1--4, 2017
Abstract:
This paper presents a robust technique, based on Krylov-subspace method, for the reduction of large-scale state-space models arising in many electromagnetic applications in fusion machines. The proposed approach, built on the Arnoldi algorithm, aims at reducing the number of states of the system and lowering the computational effort, with a negligible loss of accuracy in the numerical solution. A detailed performance study is presented on an ITER-like machine, addressing both 2-D and 3-D problems.
[ abstract ] [
url] [
pdf] [
BibTeX]
G. Michieletto, A. Cenedese, L. Zaccarian, A. Franchi.
Nonlinear Control of Multi-Rotor Aerial Vehicles Based on the Zero-Moment Direction. IFAC World Congress 2017, pp. 13686--13691, 2017
Abstract:
A quaternion-based nonlinear control strategy is here presented to steer and keep a generic multi-rotor
platform in a given reference position. Exploiting a state feedback structure, the proposed solution
ensures the stabilization of the aerial vehicle so that its linear and angular velocity are zero and its
attitude is constant. The main feature of the designed controller is the identification of a zero-moment
direction in the feasible force space, i.e., a direction along which the control force intensity can be
assigned independently of the control moment. The asymptotic convergence of the error dynamics is
confirmed by simulation results on a hexarotor with tilted propellers.
[ abstract ] [
BibTeX]
.. Et al, A. Cenedese.
Overview of the JET results in support to ITER. Nuclear Fusion, vol. 57(10), 2017
Abstract:
The 2014–2016 JET results are reviewed in the light of their significance for optimising the ITER research plan for the active and non-active operation. More than 60?h of plasma operation with ITER first wall materials successfully took place since its installation in 2011. New multi-machine scaling of the type I-ELM divertor energy flux density to ITER is supported by first principle modelling. ITER relevant disruption experiments and first principle modelling are reported with a set of three disruption mitigation valves mimicking the ITER setup. Insights of the L–H power threshold in Deuterium and Hydrogen are given, stressing the importance of the magnetic configurations and the recent measurements of fine-scale structures in the edge radial electric. Dimensionless scans of the core and pedestal confinement provide new information to elucidate the importance of the first wall material on the fusion performance. H-mode plasmas at ITER triangularity (H??=??1 at ? N ~ 1.8 and n/n GW ~ 0.6) have been sustained at 2 MA during 5?s. The ITER neutronics codes have been validated on high performance experiments. Prospects for the coming D–T campaign and 14 MeV neutron calibration strategy are reviewed.
[ abstract ] [
url] [
BibTeX]
D. Badocco, N. Trivellin, D. Barbisan, A. Cenedese, P. Pastore.
Prototype of an optical sensor for oxygen measurements in oenological matrix. Recenti sviluppi in Scienze delle Separazioni e Bioanalitica, 2017
Abstract:
The control and optimization of oxygen content in wine matrices is becoming more and more important in wine production in order to guarantee their best quality. It is well known that in a first phase O2 is necessary to facilitate the development and activity of yeasts, to favor the combination of anthocyanins and color stabilization, and to help reducing the astringency of red wines. In a second phase, however, during the maturation, O2 can severely deteriorate the organoleptic characteristics of the wine. The main oenological practices commonly performed in wine cellars causes remarkable amounts of oxygen to dissolve in wine. For this reason, an instrumentation able to be used in cellars is needed to detect the amount of dissolved oxygen in the wine; as well, a plant technology is needed which is capable of eliminating excess oxygen.
In this work, a new economic prototype of optical sensor for oxygen measurements in oenological matrices is developed. It is based on the sampling of the light emission of a polysulfone polymer membrane containing 5,10,15,20-Tetraphenyl-21H,23H-porphyrin platinum (II) (PtTPP). The experimental parameter used for calibration of the sensor is the life time of the PtTPP, obtained from the fitting of the emission decay profile produced by stimulation of the membrane with short pulses emitted by a 390 nm excitation LED. The membrane guarantees a linear behavior of the Stern-Volmer equation and long-lasting signal stability [1,2]. Studies on the behavior of the sensor have been performed in different environments such as air, water, synthetic wine, and also in real red and white wine samples at different temperatures from 5 ° to 20 ° C. The sensor has been suitably designed to work in food matrices and to optimize the noise signal ratio, while keeping the price of the components as low as possible.
The sensor was tested for a month within a barrel of 10 m containing wine in the first fermentation phase. In particular, two equal sensors were placed at two levels of depth compared to the wine infeed level: at 0.5 and 2.5 m, respectively. The oxygen content measured during this period was always constant and equal to 0.2%.
We thank Smart Future S.r.l. and the project "WOW: DEPLOYMENT OF WSAN TECHNOLOGY FOR MONITORING OXYGEN IN WINE PRODUCTS" financed by the Veneto Region ex LR 5/2001 - ex LR 9/2007.
[ abstract ] [
BibTeX]
G.A. Susto, A. Cenedese, M. Terzi.
Big Data Application in Power Systems - Ch. 2.5. Time Series Classication Methods: Review and Applications to Power Systems Data. 2017
Abstract:
The diffusion in Power Systems of distributed renewable energy resources, electric vehicles and controllable loads has made advanced monitoring systems fundamental to cope with the consequent disturbances in power flows; advanced monitoring systems can be employed for Anomaly Detection, Root Cause Analysis and Control purposes.
Several Machine Learning-based approaches have been developed in the past recent years to detect if a power system is running under anomalous conditions and, eventually, to classify such situation with respect to known problems.
One of the aspects that makes Power Systems challenging to be tackled, is that the monitoring has to be performed on streams of data that have a time series evolution; this issue is generally tackled by performing a features extraction procedure before the classication phase. The features extraction phase consists of translating the informative content of time series data into scalar quantities: such procedure may be a time-consuming step that requires the involvement of process experts to avoid loss of information in the making; moreover, extracted features designed to capture certain behaviors of the system, may not be informative under unseen conditions leading to poor monitoring performances.
A different type of data-driven approaches, that will be reviewed in this chapter, allow to perform classication directly on the raw time series data, avoiding the features extraction phase: among these approaches, Dynamic Time Warping and Symbolic-based methodologies have been widely applied in many application areas.
In the following, pros and cons of each approach will be discussed and practical implementation guidelines will be provided.
[ abstract ] [
url] [
BibTeX]
2016
A. Cenedese, M. Fagherazzi, P. Bettini.
A Novel Application of Selective Modal Analysis to Large-Scale Electromagnetic Devices. IEEE Transactions on Magnetics, vol. 52(3), pp. 1--4, 2016
Abstract:
In the analysis and design of large-scale dynamical systems, model reduction techniques aim at yielding a reasonable trade-off
between the contrasting needs of reducing the number of states and of reaching a good approximation of the overall system behavior.
In the specific case of complex electromagnetic devices, a large number of state variables represent physical quantities in the overall
system. This work collocates along this line of research and aims at studying Model Order Reduction techniques that maintain the
mathematical formalism of system theory but at the same time keep consistency with the physics of the phenomena of interest.
[ abstract ] [
url] [
BibTeX]
A. Cenedese, G.A. Susto, M. Terzi.
A Parsimonious Approach for Activity Recognition with Wearable Devices: an Application to Cross-country Skiing. European Control Conference 2016 (ECC'16), pp. 2541-2546, 2016
Abstract:
With the aim of monitoring the human activity,
wearable devices provide an enhanced usability and a seamless
human experience with respect to other portable devices (e.g.
smartphones) in critical tasks as well as in leisure and sport
activities. At the same time, though, wearable devices are more
resource-constrained in terms of computational capability and
memory, which calls for the design of algorithmic solutions
that explicitly take into account these issues. In this paper, a
parsimonious approach for activity recognition with wearable
devices is presented. The methodology is based on Relevant
Vector Machines (RVMs), a sparse machine learning framework
for classification, and allows to tackle the activity recognition
problem by identifying the two phases of Event Identification
and Gesture Recognition. The performance of the presented
methodology is tested on the interesting case study of cross-
country skiing (classic style): such a dataset presents three
different classes of gestures in addition to non-gesture activities
and has been obtained by recording the training sessions
of a heterogeneous set of executors in different environment
conditions.
[ abstract ] [
url] [
BibTeX]
A. Cenedese, L. Minetto, G.A. Susto, M. Terzi.
A Symbolic Approach to Human Activity Recognition. 5th International Workshop on Symbiotic Interaction, 2016
Abstract:
In the context of activity recognition, wearable devices arenowadays the preferable hardware thanks to their usability, user expe-rience and performances; at the same time, these devices present limi-tations in terms of computational capability and memory, which forcethe algorithm design to be at the same time ecient and simple. Inthis work, we adopt Symbolic Aggregate Approximation (SAX), a sym-bolic approach for information retrieval in time series data that allowsdimensionality and numerosity reduction; SAX is employed here, in com-bination with 1-Nearest Neighbor classier, to identify activity phases incontinuous repetitive activities from inertial time-series data. The pro-posed approach is validated on a public activity recognition dataset.
[ abstract ] [
BibTeX]
S. Borile, A. Pandharipande, D. Caicedo, A. Cenedese, L. Schenato.
An identification approach to lighting control. European Control Conference 2016 (ECC'16), pp. 637-642, 2016
Abstract:
The problem of daylight estimation in a smart lighting system is considered. The smart lighting system consists of multiple luminaires with collocated occupancy and light sensors. Using sensor information, the objective is to attain illumination levels higher than specified values at the workspaces. We consider a training phase wherein light sensors are used at the workspaces in addition. Data from the light sensors at the ceiling and workspaces is used to estimate the mapping across the sensors. In the operational phase, the estimated mapping is used at the lighting controller to obtain an estimate of the illuminance value at the workspaces. Under the constraint that the estimated illuminance is higher than a specified target value, the controller optimizes the dimming levels of the luminaires to minimize power consumption. We evaluate the performance of the proposed approach in an open-office lighting model by considering different daylight conditions.
[ abstract ] [
url] [
BibTeX]
G. Michieletto, A. Cenedese, A. Franchi.
Bearing Rigidity Theory in SE(3). 55th Conference on Decision and Control (CDC16), pp. 5950-5955, 2016
Abstract:
Recently, rigidity theory has emerged as an ef-
ficient tool in the control field of coordinated multi–agent
systems, such as multi–robot formations and UAVs swarms
that are characterized by the sensing, communication and
movement capabilities. This paper aim at describing the rigidity
properties for frameworks embedded in SE(3), i.e. the three–
dimensional Euclidean space wherein each agent has 6DoF. In
such configuration, it is assumed that the devices are able to
gather bearing measurements of their neighbors, expressing
them into their own body frame. Rigidity properties are
mathematically formalized in the paper which differs from the
previous works as it faces the extension in three–dimensional
space dealing with the 3D rotations manifold. In particular,
the attention is focused on the infinitesimal SE(3)–rigidity for
which necessary and sufficient condition is provided.
[ abstract ] [
url] [
BibTeX]
G. Belgioioso, A. Cenedese, G. Michieletto.
Distributed partitioning strategies with visual optimization for camera network perimeter patrolling. 55th Conference on Decision and Control (CDC16), pp. 5912-5917, 2016
Abstract:
The employment of smart camera networks for
surveillance purposes has become ubiquitous in many appli-
cation scenarios, from the industrial, to the public, to the
home environments. In particular, in this work the boundary
patrolling problem is considered, where the camera network task
is to monitor the perimeter of an environment so as to detect
anomalies and track possible intrusions. Here, a distributed
solution is sought based on the definition of a suitable functional
that accounts both for the equitable partitioning of the available
space and for the quality of vision of the patrolled area,
and admits a unique optimal solution. The optimization of
such functional leads to the design of an algorithm relying
on a symmetric gossip communication protocol among the
neighboring cameras. The theoretical results formalized in
terms of propositions prove the correctness of the approach
and the numerical simulations on a realistic scenario confirm
the validity of the proposed procedure.
[ abstract ] [
url] [
BibTeX]
A. Cenedese, L. Minetto, G.A. Susto, M. Terzi.
Human Activity Recognition with Wearable Devices: A Symbolic Approach. PsychNology, vol. 14(2-3), pp. 99-115, 2016
Abstract:
In the context of activity recognition, wearable devices are nowadays the preferable hardware
thanks to their usability, user experience and performances; at the same time, these devices
present limitations in terms of computational capability and memory, which force the algorithm
design to be at the same time efficient and simple. In this work, we adopt Symbolic Aggregate
Approximation (SAX), a symbolic approach for information retrieval in time series data that
allows dimensionality and numerosity reduction; SAX is employed here, in combination with
1-Nearest Neighbor classifier, to identify activity phases in continuous repetitive activities from
inertial time-series data. The proposed approach is validated on a cross-country skiing dataset
and on a daily living activities dataset.
[ abstract ] [
url] [
BibTeX]
M. Bonotto, P. Bettini, A. Cenedese.
Model order reduction of large-scale state-space models in fusion machines via Krylov methods. 17th IEEE Conference on Electromagnetic Field Computation (CEFC16), 2016
Abstract:
This work presents a robust technique, based on the
Krylov subspace method, for the reduction of large-scale state-
space models arising in many electromagnetic problems in fusion
machines. The proposed approach aims at reducing the number
of states of the system and lowering the computational effort,
with a negligible loss of accuracy in the numerical solution. It is
built on the Arnoldi algorithm, which allows to avoid numerical
instabilities when computing the reduced model, and exploits
both input/output Krylov methods. In the full paper a detail
performance study will be presented on an ITER-like machine.
[ abstract ] [
url] [
BibTeX]
A. Cenedese, C. Favaretto, G. Occioni.
Multi-agent Swarm Control through Kuramoto Modeling. 55th Conference on Decision and Control (CDC16), pp. 1820-1825, 2016
Abstract:
In this paper we discuss a particular case of
synchronization involving a finite population of nonlinearly
coupled oscillators. We employ a discrete time approximation of
the Kuramoto model in order to achieve the coordination of the
heading directions of N identical vehicles moving at constant
speed in a bidimensional environment; this synchronization
model acts as a base for a more complex distributed control, the
aim of which is to direct the vehicles towards a target, adjusting
their trajectories alongside their formation in the process, while
avoiding collisions.
[ abstract ] [
url] [
BibTeX]
D. Varagnolo, F. Zanella, A. Cenedese, G. Pillonetto, L. Schenato.
Newton-Raphson Consensus for Distributed Convex Optimization. IEEE Transactions on Automatic Control, vol. 61(4), pp. 994--1009, 2016
Abstract:
We address the problem of distributed unconstrained convex optimization under separability assumptions, i.e., the framework where a network of agents, each endowed with local private multidimensional convex cost and subject to communication constraints, wants to collaborate to compute the minimizer of the sum of the local costs. We propose a design methodology that combines average consensus algorithms and separation of time-scales ideas. This strategy is proven, under suitable hypotheses, to be globally convergent to the true minimizer. Intuitively, the procedure lets the agents distributedly compute and sequentially update an approximated Newton-Raphson direction by means of suitable average consensus ratios. We show with numerical simulations that the speed of convergence of this strategy is comparable with alternative optimization strategies such as the Alternating Direction Method of Multipliers. Finally, we propose some alternative strategies which trade-off communication and computational requirements with convergence speed.
[ abstract ] [
url] [
pdf] [
BibTeX]
C. Favaretto, A. Cenedese.
On brain modeling in resting-state as a network of coupled oscillators. 55th Conference on Decision and Control (CDC16), pp. 4190-4195, 2016
Abstract:
The problem of emergent synchronization pat-terns in a complex network of coupled oscillators has caughtscientists’ interest in a lot of different disciplines. In particular,from a biological point of view, considerable attention has beenrecently devoted to the study of the human brain as a networkof different cortical regions that show coherent activity duringresting-state. In literature, there can be found different large-scale models of resting-state dynamics in health and disease.In this context, the Kuramoto model, a classical model apt todescribe oscillators’ dynamics, has been extended to capture thespatial displacement and the communication conditions in suchbrain network. Starting from a previous work in this ?eld ,we analyze this modi?ed model and compare it with otherexisting large-scale models. In doing so, our aim is to promotea set of mathematical tools useful to better understand realexperimental data in neuroscience and estimate brain dynamics.
[ abstract ] [
url] [
BibTeX]
2015
A. Pandharipande, M. Rossi, D. Caicedo, L. Schenato, A. Cenedese.
Centralized lighting control with luminaire-based occupancy and light sensing. Proc. of the IEEE Int. Conf. on Industrial Informatics 2015 (INDIN 2015), pp. CD-007153, 2015
Abstract:
We consider control of multiple luminaires with a
central controller and distributed occupancy and light sensors
co-located at the luminaires. The sensors periodically provide
local occupancy state and illumination information to the central
controller. Using this sensor feedback, the central controller
determines the dimming levels of the luminaires so as to adapt
artificial light output to changing daylight levels and occupancy
conditions, in an energy efficient way. We propose a multi-
variable feedback controller and compare its performance with
a simple stand-alone proportional-integral controller. We show
via simulations in an open-plan office lighting system that the
proposed controller has better performance in terms of achieving
the reference set-points.
[ abstract ] [
url] [
BibTeX]
G. Bianchin, A. Cenedese, M. Luvisotto, G. Michieletto.
Distributed Fault Detection in Sensor Networks via Clustering and Consensus. 54th Conference on Decision and Control (CDC15), pp. 3828--3833, 2015
Abstract:
In this paper we address the average consensus problem in a Wireless Sensor-Actor Network with the particular focus on autonomous fault detection. To this aim, we design a distributed clustering procedure that partitions the network into clusters according to both similarity of measurements and communication connectivity. The exploitation of clustering techniques in consensus computation allows to obtain the detection and isolation of faulty nodes, thus assuring the convergence of the other nodes to the exact consensus value. More interestingly, the algorithm can be integrated into a Kalman filtering framework to perform distributed estimation of a dynamic quantity in presence of faults. The proposed approach is validated through numerical simulations and tests on a real world scenario dataset.
[ abstract ] [
url] [
BibTeX]
A. Cenedese, G.A. Susto, G. Belgioioso, G.I. Cirillo, F. Fraccaroli.
Home Automation Oriented Gesture Classification From Inertial Measurements. IEEE Transactions on Automation Science and Engineering, vol. 12(4), pp. 1200--1210, 2015
Abstract:
In this paper, a Machine Learning (ML) approach is presented that exploits accelerometers data to deal with gesture recognition (GR) problems. The proposed methodology aims at providing high accuracy classi?cation for Home Automation systems, which are generally user independent, device independentand device orientation independent, an heterogeneous scenario that was not fully investigated in previous GR literature. The approach illustrated in this work is composed of three main steps: event identi?cation, feature extraction and ML-based classi?cation; elements of novelty of the proposed approach are:
1. a pre-processing phase based on Principal Component Analysis to increase the performance in real-world scenario conditions;
2.the development of parsimonious novel classi?cation techniques based on Sparse Bayesian Learning.
This methodology is tested on two datasets of 4 gesture classes (horizontal, vertical, circles and eight-shaped movements) and on a further dataset with 8 classes. In order to authentically describe a real-world Home Automation environment, the gesture movements are collected from more than 30 people who freely perform any gesture. It results a dictionary of 12 and 20 different movements respectivelyin the case of the 4-class and the 8-class databases.
[ abstract ] [
url] [
BibTeX]
A. Cenedese, M. Fagherazzi, P. Bettini.
Model Reduction Techniques for the Analysis and the Design of Large-Scale Electromagnetic Devices. Proceedings of the Conference on the Computation of Electromagnetic Fields (COMPUMAG 2015), pp. PC4 - 7, 2015
Abstract:
In the analysis and design of large-scale dynamical systems, simpler models are often preferred to full system models due to
their better suitability with computer simulations and real-time constraints. Model reduction techniques aim at yielding a reasonable
trade-off between the contrasting needs of reducing the number of states and of reaching a good approximation of the overall system
behavior. In the specific case of complex electromagnetic devices (as fusion machines) a large number of state variables represent
physical quantities in the overall system, such as currents, voltages, magnetic flux densities and so on. Since it would be important
not to loose this valuable feature while reducing the order of the system, we focus on the Selective Modal Analysis (SMA) technique
which allows to preserve this meaning resorting to a state selection according to the contribution of the single states to the model
modes. The application of various MOR techniques to the numerical models of the ITER machine is discussed.
[ abstract ] [
url] [
BibTeX]
A. Cenedese, C. Favaretto.
On the synchronization of spatially coupled oscillators. 54th Conference on Decision and Control (CDC15), pp. 4836--4841, 2015
Abstract:
Over the past decade, considerable attention has
been devoted to the problem of emergence of synchronization
patterns in a network of coupled oscillators, which can be
observed in a variety of disciplines, both in the biological and
in the engineering fields. In this context, the Kuramoto model
is a classical model for describing synchronization phenomena
that arise in large-scale systems that exploit local information
and interactions. In this work, an extension of such a model is
presented, that considers also the spatial distances among the
oscillator nodes. In particular, coupling strength and spatial
conditions are derived, needed to reach phase cohesiveness
and frequency synchronization, both in the scenario when a
single population of agents is present and when two different
populations interact. These theoretical findings are confirmed
by extensive numerical Monte Carlo simulations and statistical
analysis.
[ abstract ] [
url] [
BibTeX]
M. Rossi, A. Pandharipande, D. Caicedo, L. Schenato, A. Cenedese.
Personal lighting control with occupancy and daylight adaptation. Energy and Buildings, vol. 105pp. 263–-272, 2015
Abstract:
Personal control with occupancy and daylight adaptation is considered in
a lighting system with multiple luminaires. Each luminaire is equipped
with a co-located occupancy sensor and light sensor that respectively
provide local occupancy and illumination information to a central
controller. Users may also provide control inputs to indicate a desired
illuminance value. Using sensor feedback and user input, the central
controller determines dimming values of the luminaires using an
optimization framework. The cost function consists of a weighted sum of
illumination errors at light sensors and the power consumption of the
system. The optimum dimming values are determined with the constraints
that the illuminance value at the light sensors are above the reference
set-point at the light sensors and the dimming levels are within
physical allowable limits. Different approaches to determine the
set-points at light sensors associated with multiple user illumination
requests are considered. The performance of the proposed constrained
optimization problem is compared with a reference stand-alone controller
under different simulation scenarios in an open-plan office lighting
system.
[ abstract ] [
url] [
BibTeX]