Predictive stability filters for nonlinear dynamical systems affected by disturbances

Fuente: arXiv
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Autori principali: Didier, Alexandre, Zanelli, Andrea, Wabersich, Kim P., Zeilinger, Melanie N.
Natura: Preprint
Pubblicazione: 2024
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author Didier, Alexandre
Zanelli, Andrea
Wabersich, Kim P.
Zeilinger, Melanie N.
author_facet Didier, Alexandre
Zanelli, Andrea
Wabersich, Kim P.
Zeilinger, Melanie N.
contents Predictive safety filters provide a way of projecting potentially unsafe inputs, proposed, e.g. by a human or learning-based controller, onto the set of inputs that guarantee recursive state and input constraint satisfaction by leveraging model predictive control techniques. In this paper, we extend this framework such that in addition, robust asymptotic stability of the closed-loop system can be guaranteed by enforcing a decrease of an implicit Lyapunov function which is constructed using a predicted system trajectory. Differently from previous results, we show robust asymptotic stability with respect to a predefined disturbance set on an extended state consisting of the system state and a warmstart input sequence. The proposed strategy is applied to an automotive lane keeping example in simulation.
format Preprint
id arxiv_https___arxiv_org_abs_2401_11183
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Predictive stability filters for nonlinear dynamical systems affected by disturbances
Didier, Alexandre
Zanelli, Andrea
Wabersich, Kim P.
Zeilinger, Melanie N.
Systems and Control
Optimization and Control
Predictive safety filters provide a way of projecting potentially unsafe inputs, proposed, e.g. by a human or learning-based controller, onto the set of inputs that guarantee recursive state and input constraint satisfaction by leveraging model predictive control techniques. In this paper, we extend this framework such that in addition, robust asymptotic stability of the closed-loop system can be guaranteed by enforcing a decrease of an implicit Lyapunov function which is constructed using a predicted system trajectory. Differently from previous results, we show robust asymptotic stability with respect to a predefined disturbance set on an extended state consisting of the system state and a warmstart input sequence. The proposed strategy is applied to an automotive lane keeping example in simulation.
title Predictive stability filters for nonlinear dynamical systems affected by disturbances
topic Systems and Control
Optimization and Control
url https://arxiv.org/abs/2401.11183