Nonpathological ISS-Lyapunov Functions for Interconnected Differential Inclusions
Matteo Della Rossa (LAAS-MAC), Aneel Tanwani (LAAS-MAC), Luca, Zaccarian

TL;DR
This paper develops less conservative ISS stability conditions for interconnected systems modeled by differential inclusions using non-smooth Lyapunov functions and generalized derivatives, with applications to switched systems.
Contribution
It introduces new ISS conditions for differential inclusions using locally Lipschitz Lyapunov functions and Lie generalized derivatives, improving upon traditional Clarke derivative methods.
Findings
Provided sufficient ISS conditions for differential inclusions.
Applied results to state-dependent switched systems.
Demonstrated an observer-based controller for nonlinear switched systems.
Abstract
This article concerns robustness analysis for interconnections of two dynamical systems (described by upper semicontinuous differential inclusions) using a generalized notion of derivatives associated with locally Lipschitz Lyapunov functions obtained from a finite family of differentiable functions. We first provide sufficient conditions for input-to-state stability (ISS) for differential inclusions, using a class of non-smooth (but locally Lipschitz) candidate Lyapunov functions and the concept of Lie generalized derivative. In general our conditions are less conservative than the more common Clarke derivative based conditions. We apply our result to state-dependent switched systems, and to the interconnection of two differential inclusions. As an example, we propose an observer-based controller for certain nonlinear two-mode state-dependent switched systems.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStability and Control of Uncertain Systems · Control and Stability of Dynamical Systems · Neural Networks Stability and Synchronization
