|Time:||October 31, 2023|
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Tim Martin, M.Sc.
Institute for Systems Theory and Automatic Control
University of Stuttgart
Tuesday 2023-10-31 4 p.m.
IST Seminar Room 2.255 - Pfaffenwaldring 9 - Campus Stuttgart-Vaihingen
The verification of control-theoretic properties and the design of controllers usually require the knowledge of a model of the underlying dynamical system for which the identification is often time-consuming and calls for expert knowledge on the physical phenomena. Hence, the interests on data-driven techniques to deduce system properties and controllers without identifying a model but directly from measured trajectories of the system have risen. Our approach includes a data-based representation of nonlinear systems which combines multiple set memberships for interpolation polynomials. By incorporating the measurement noise and the error by polynomial approximation, we verify dissipativity properties and derive robust controllers from finite noisy samples with rigorous stability and performance guarantees. Furthermore, the application of sum-of-squares relaxation leads to computationally tractable conditions despite nonlinear system dynamics.
Tim Martin received the master’s degree in Engineering Cybernetics from the University of Stuttgart in 2018. During his studies he spent 6 months at ITK Engineering for an internship. Since 2018, he has been a research and teaching assistant at the Institute for Systems Theory and Automatic Control and a doctoral student in the Graduate School Simulation Technology at the University of Stuttgart. In 2022, he spent three months as a visiting researcher at the Department of Information Technology, Uppsala University. His research interests include data-driven system analysis and control with focus on nonlinear systems.