# Action Governor for Discrete-Time Linear Systems with Non-Convex Constraints

arXiv: https://arxiv.org/abs/2005.08358 · HTML: https://mlsanity.com/paper/2005.08358/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 May 2020.

## Built on by (most cited first, 3 of 3)

- [Safe Reinforcement Learning Using Robust Action Governor](https://mlsanity.com/paper/2102.10643/) (2021)
- [Robust Action Governor for Uncertain Piecewise Affine Systems with Non-convex Constraints and Safe Reinforcement Learning](https://mlsanity.com/paper/2207.08240/) (2022)
- [Safe Control and Learning Using Generalized Action Governor](https://mlsanity.com/paper/2211.12628/) (2022)

## Abstract (arXiv)

This paper introduces an add-on, supervisory scheme, referred to as Action Governor (AG), for discrete-time linear systems to enforce exclusion-zone avoidance requirements. It does so by monitoring, and minimally modifying when necessary, the nominal control signal to a constraint-admissible one. The AG operates based on set-theoretic techniques and online optimization. This paper establishes its theoretical foundation, discusses its computational realization, and uses two simulation examples to illustrate its effectiveness.