30/10/2024
11:00
A hybrid systems framework for data-based adaptive control of linear time-varying systems
Scuola IMT Alti Studi Lucca
DYSCO
Lucca
 (Lucca)
 - Toscana
Piazza San Francesco 19, Lucca
Piazza S. Francesco Complex - Classroom 2
Pubblico

In this talk, we consider the data-driven stabilization of discrete-time linear time-varying systems when the model of the plant is unknown. The controller is defined as a linear state-feedback that adapts to the plant's changes in an event-triggered fashion using a data-based condition. As a result, the resulting closed-loop dynamics exhibits both physical jumps, due to the system dynamics, and episodic jumps, due to the feedback update, which leads to a hybrid discrete-time system description. This representation provides a natural setting for designing events which trigger the controller update when this becomes necessary due to the plant’s variations, as well as formally analyzing the closed-loop properties of this feedback interconnection. Leveraging the inherent robustness of the feedback gain synthesised based on the last collected, we provide general conditions under which various stability notions can be established for the closed-loop system, and discuss two particular cases where they are satisfied. We conclude by providing numerical results that illustrate the relevance of the proposed approach.

BIO: Andrea Iannelli is a tenure-track assistant professor in the Institute for Systems Theory and Automatic Control at the University of Stuttgart. He completed his B.Sc. and M.Sc. degrees in Aerospace Engineering at the University of Pisa (Italy) and received his PhD from the University of Bristol (United Kingdom), where he worked on robust control and dynamical systems theory. He was a postdoctoral researcher in the Automatic Control Laboratory at ETH Zürich (Switzerland). His main research interests are at the intersection of control theory, optimization, and learning, with a particular focus on robust and adaptive optimization-based control, uncertainty quantification, and sequential decision-making problems. He serves the community as Associated Editor for the International Journal of Robust and Nonlinear Control and as IPC member of international conferences in the areas of control, optimization, and learning.

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