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arXiv · 2206.11176

Counterexample-guided computation of polyhedral Lyapunov functions for hybrid systems

Guillaume O. Berger·Sriram Sankaranarayanan
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Abstract

This paper presents a counterexample-guided iterative algorithm to compute convex, piecewise linear (polyhedral) Lyapunov functions for uncertain continuous-time linear hybrid systems. Polyhedral Lyapunov functions provide an alternative to commonly used polynomial Lyapunov functions. Our approach first characterizes intrinsic properties of a polyhedral Lyapunov function including its "eccentricity" and "robustness" to perturbations. We then derive an algorithm that either computes a polyhedral Lyapunov function proving that the system is stable, or concludes that no polyhedral Lyapunov function exists whose eccentricity and robustness parameters satisfy some user-provided limits. Significantly, our approach places no a priori bounds on the number of linear pieces that make up the desired polyhedral Lyapunov function. The algorithm alternates between a learning step and a verification step, always maintaining a finite set of witness states. The learning step solves a linear program to compute a candidate Lyapunov function compatible with a finite set of witness states. In the verification step, our approach verifies whether the candidate Lyapunov function is a valid Lyapunov function for the system. If verification fails, we obtain a new witness. We prove a theoretical bound on the maximum number of iterations needed by our algorithm. We demonstrate the applicability of the algorithm on numerical examples.

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BibTeXRIS

Guillaume O. Berger, Sriram Sankaranarayanan. 2022-06-22. Counterexample-guided computation of polyhedral Lyapunov functions for hybrid systems. https://arxiv.org/abs/2206.11176

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