A Frequency-Domain Approach for Data-Driven Control of Nonlinear Systems with Global Guarantees
Event details
| Date | 21.04.2023 |
| Hour | 11:00 › 12:00 |
| Speaker | Prof. Roland Toth, Eindhoven University of Technology, The Netherlands |
| Location |
ME C2 405
|
| Category | Conferences - Seminars |
| Event Language | English |
Abstract: Originally, the linear parameter-varying (LPV) framework has been introduced with the intention to systematically design gain-scheduled controllers for nonlinear systems based on local data. However, local representations of the nonlinear system were not sufficient to guarantee stability and performance for arbitrary scheduling variations, which has led to the introduction of more complicated global LPV embedding based control design. In this talk, we show that the underlying difficulties can be overcome by new advances of nonlinear control theory in terms of the so-called velocity form of the nonlinear system and the connected notions of universal shifted stability and dissipativity. Based on this insight, we present a data-based control design method for nonlinear systems, based on local frequency-domain data, with equilibrium independent stability and performance guarantees. To this end, we show how frequency response functions (FRFs) of the velocity form of a nonlinear system can be identified using local or time-varying observations. Using these FRFs, a data-driven controller synthesis concept is presented to design an LPV controller in the velocity domain. By accomplishing a realization step, a nonlinear controller is computed from the LPV design that ensures equilibrium independent stability and performance of the closed-loop system. The effectiveness of the proposed method is demonstrated on a simulation example.
Bio: Roland Toth received his Ph.D. degree with Cum Laude distinction at the Delft Center for Systems and Control (DCSC), Delft University of Technology (TUDelft) in 2008. He was a Post-Doctoral Research Fellow at TUDelft in 2009 and at the Berkeley Center for Control and Identification, University of California, Berkeley in 2010. He held a position at DCSC, TUDelft in 2011-12, then he joined to the Control Systems (CS) Group at the Eindhoven University of Technology (TU/e). Currently, he is an Associate Professor at the CS Group, TU/e and a senior researcher at the Systems and Control Laboratory, Institute for Computer Science and Control (SZTAKI) in Budapest, Hungary. He is an Associate Editor of the IEEE Transactions on Control Systems Technology and he was the general chair of the 3rd IFAC Workshop on Linear Parameter-Varying Systems in 2019.
His research interests are in identification and control of linear parameter-varying (LPV) and nonlinear systems, developing machine learning methods with performance and stability guarantees for modeling and control, model predictive control and behavioral system theory. On the application side, his research focuses on advancing reliability and performance of precision mechatronics and autonomous robots/vehicles with LPV and learning-based motion control.
Dr. Toth received the TUDelft Young Researcher Fellowship Award in 2010, the VENI award of The Netherlands Organisation for Scientific Research in 2011 and the Starting Grant of the European Research Council in 2016. He and his research team has participated in several international (FP7, IT2-ESCEL, etc.) and national collaborative research projects.
Bio: Roland Toth received his Ph.D. degree with Cum Laude distinction at the Delft Center for Systems and Control (DCSC), Delft University of Technology (TUDelft) in 2008. He was a Post-Doctoral Research Fellow at TUDelft in 2009 and at the Berkeley Center for Control and Identification, University of California, Berkeley in 2010. He held a position at DCSC, TUDelft in 2011-12, then he joined to the Control Systems (CS) Group at the Eindhoven University of Technology (TU/e). Currently, he is an Associate Professor at the CS Group, TU/e and a senior researcher at the Systems and Control Laboratory, Institute for Computer Science and Control (SZTAKI) in Budapest, Hungary. He is an Associate Editor of the IEEE Transactions on Control Systems Technology and he was the general chair of the 3rd IFAC Workshop on Linear Parameter-Varying Systems in 2019.
His research interests are in identification and control of linear parameter-varying (LPV) and nonlinear systems, developing machine learning methods with performance and stability guarantees for modeling and control, model predictive control and behavioral system theory. On the application side, his research focuses on advancing reliability and performance of precision mechatronics and autonomous robots/vehicles with LPV and learning-based motion control.
Dr. Toth received the TUDelft Young Researcher Fellowship Award in 2010, the VENI award of The Netherlands Organisation for Scientific Research in 2011 and the Starting Grant of the European Research Council in 2016. He and his research team has participated in several international (FP7, IT2-ESCEL, etc.) and national collaborative research projects.
Practical information
- General public
- Free