Inverse-Optimal Safety Control for Hybrid Systems

We study control design methods to endow hybrid systems under disturbances with safety guarantees as an inverse-optimality problem. First, we provide sufficient conditions to guarantee input-to-state safety of a hybrid system with disturbance inputs only. Next, given a nominal feedback law, we show that a hybrid system, with inputs and disturbances, can be rendered input-to-state controlled safe under the existence of a control barrier function (CBF) using pointwise min-norm safeguarding feedback laws. Finally, we demonstrate that every CBF is a meaningful value function for a two-player zero-sum hybrid game in the context of safety, and that every pointwise min-norm safeguarding feedback law is optimal for such a game, even though its design is independent of any cost functional. The main results are illustrated in an example.

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Publication Details

Published
2025-05-06
DOI
https://doi.org/10.1145/3716863.3718044
Citations
1
Primary Topic
Advanced Control Systems Optimization
Type
article
Field-Weighted Citation Impact
1.21

Funders

Controls
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article

Inverse-Optimal Safety Control for Hybrid Systems

Santiago J. Leudo, Ricardo G. Sanfelice, Carlos A. Montenegro G.
1 citations
Advanced Control Systems Optimization
1.21
article

Inverse-Optimal Safety Control for Hybrid Systems

Santiago J. Leudo, Ricardo G. Sanfelice, Carlos A. Montenegro G.
article en
1 citations

Abstract

We study control design methods to endow hybrid systems under disturbances with safety guarantees as an inverse-optimality problem. First, we provide sufficient conditions to guarantee input-to-state safety of a hybrid system with disturbance inputs only. Next, given a nominal feedback law, we show that a hybrid system, with inputs and disturbances, can be rendered input-to-state controlled safe under the existence of a control barrier function (CBF) using pointwise min-norm safeguarding feedback laws. Finally, we demonstrate that every CBF is a meaningful value function for a two-player zero-sum hybrid game in the context of safety, and that every pointwise min-norm safeguarding feedback law is optimal for such a game, even though its design is independent of any cost functional. The main results are illustrated in an example.

University of California, Santa Cruz (US)
National Science Foundation, Air Force Office of Scientific Research, Army Research Office, Air Force Research Laboratory
Affordable and clean energy
Openalex Percentile: Top 21%
Advanced Control Systems Optimization
1.21
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