Finite-Step Invariant Sets for Hybrid Systems with Probabilistic Guarantees

Fuente: arXiv
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Main Authors: Madabushi, Varun, Dietrich, Elizabeth, Krasowski, Hanna, Tucker, Maegan
Format: Preprint
Published: 2026
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author Madabushi, Varun
Dietrich, Elizabeth
Krasowski, Hanna
Tucker, Maegan
author_facet Madabushi, Varun
Dietrich, Elizabeth
Krasowski, Hanna
Tucker, Maegan
contents Poincare return maps are a fundamental tool for analyzing periodic orbits in hybrid dynamical systems, including legged locomotion, power electronics, and other cyber-physical systems with switching behavior. The Poincare return map captures the evolution of the hybrid system on a guard surface, reducing the stability analysis of a periodic orbit to that of a discrete-time system. While linearization provides local stability information, assessing robustness to disturbances requires identifying invariant sets of the state space under the return dynamics. However, computing such invariant sets is computationally difficult, especially when system dynamics are only available through forward simulation. In this work, we propose an algorithmic framework leveraging sampling-based optimization to compute a finite-step invariant ellipsoid around a nominal periodic orbit using sampled evaluations of the return map. The resulting solution is accompanied by probabilistic guarantees on finite-step invariance satisfying a user-defined accuracy threshold. We demonstrate the approach on two low-dimensional systems and a compass-gait walking model.
format Preprint
id arxiv_https___arxiv_org_abs_2604_05102
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Finite-Step Invariant Sets for Hybrid Systems with Probabilistic Guarantees
Madabushi, Varun
Dietrich, Elizabeth
Krasowski, Hanna
Tucker, Maegan
Systems and Control
Robotics
Poincare return maps are a fundamental tool for analyzing periodic orbits in hybrid dynamical systems, including legged locomotion, power electronics, and other cyber-physical systems with switching behavior. The Poincare return map captures the evolution of the hybrid system on a guard surface, reducing the stability analysis of a periodic orbit to that of a discrete-time system. While linearization provides local stability information, assessing robustness to disturbances requires identifying invariant sets of the state space under the return dynamics. However, computing such invariant sets is computationally difficult, especially when system dynamics are only available through forward simulation. In this work, we propose an algorithmic framework leveraging sampling-based optimization to compute a finite-step invariant ellipsoid around a nominal periodic orbit using sampled evaluations of the return map. The resulting solution is accompanied by probabilistic guarantees on finite-step invariance satisfying a user-defined accuracy threshold. We demonstrate the approach on two low-dimensional systems and a compass-gait walking model.
title Finite-Step Invariant Sets for Hybrid Systems with Probabilistic Guarantees
topic Systems and Control
Robotics
url https://arxiv.org/abs/2604.05102