Industrial Control Applications

The research activity mostly concerns the development of models and control algorithms for vehicles and vehicle components. Special emphasis is given on the use of virtual prototyping tools, including hardware- and human-in-the-loop tools. The activity is focused on three main topics:

• Design of control algorithms for virtual vehicles for prototyping applications

• Design of vehicle pose estimation algorithms

• Design of motion cueing algorithms for car driving simulators

Efficient use of energy is one of the main strategic measures not only for the conservation of fossil energy resources but also for abatement of air pollution and the slowing down of anthropogenic climate change. The requirement of primary energy to cool and to heat buildings is an important part of the overall energy consumption in Western countries, summing up to about 30% of the U.S. and European global energy consumption, due to the increasing use of air conditioning units for cooling residential and office buildings during summer. The European Commission deliberated on the energy performance of buildings (EPBD), with the Directive 2002/91/EC, which imposes several actions to achieve prudent and rational use of energy resources and to reduce the environmental impact of the energy use in buildings.

This can be accomplished by increasing both the energy performance of new and existing buildings and the efficiency of cooling/heating systems. Advanced control methodologies can be applied to HVAC system management in order to improve energy efficiency, and regulation performance.

Machine Learning and Control for Industry 4.0

The so-called '4th Industrial Revolution' is making disruptive changes in manufacturing, product development and business process management. This revolution is centered around the availability of data and their exploitation. Machine Learning and Control approaches provide the methodological tools to take advantage of such data for reducing costs, optimize processes and operation, increase productivity and uptime and much more. 

The research activity of the group covers Anomaly/Fault Detection, Computer Vision for Defect Detection, Statistical & Advanced Process Control, Virtual Metrology & Soft Sensing, and Predictive Maintenance issues.

The research focuses on industrial communication networks, that are real-time communication systems deployed in several application contexts such as, for example, factory automation, motion control, process automation, networked control systems, building automation and automotive systems; in the last few years novel paradigms for the industrial communication systems have emerged such as those of the time sensitive networks (TNT) and the industrial Internet of things (IIOT)

These specific types of networks have to cope with the tight requirements typical of the industrial scenario. Particularly, they have to provide real-time performance as well as high reliability and robustness. The main research topics are the following:

• Real-time communication protocols design

• Protocol modeling

• Performance analysis

• Practical tests on prototype systems

Homepage: http://automatica.dei.unipd.it/research.html

Tokamaks are among the most promising devices for obtaining nuclear fusion energy from a high-temperature, ionized gas (plasma).

In tokamaks, plasma is confined within a magnetic cage created by active magnetic fields inside a doughnut shaped metallic chamber; a current (of MA intensity) is induced in the plasma by transformer action and toroidal and poloidal field coils are fed with high intensity currents (hundreds of kA) to produce strong fields that provide plasma equilibrium and stability, and control the mass position and shape. 

This complex and demanding application requires estimation and regulation systems to provide robust reconstruction of the geometry and internal features of the plasma inside the chamber, and real time control to drive the plasma through different phases along the discharge evolution and thus guarantee the nuclear reaction performances. 

Ongoing specific research topics regard:

• Plasma dynamic modeling and model order reduction

• Design of algorithms for real time plasma boundary reconstruction

• Optimal sensor selection

Homepage: http://automatica.dei.unipd.it/people/cenedese/research/fpmc.html

People: Alessandro Beghi, Angelo Cenedese (contact person)