Cooptimizing Safety and Performance with a Control-Constrained Formulation

Fuente: arXiv
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Main Authors: Wang, Hao, Dhande, Adityaya, Bansal, Somil
Format: Preprint
Published: 2024
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author Wang, Hao
Dhande, Adityaya
Bansal, Somil
author_facet Wang, Hao
Dhande, Adityaya
Bansal, Somil
contents Autonomous systems have witnessed a rapid increase in their capabilities, but it remains a challenge for them to perform tasks both effectively and safely. The fact that performance and safety can sometimes be competing objectives renders the cooptimization between them difficult. One school of thought is to treat this cooptimization as a constrained optimal control problem with a performance-oriented objective function and safety as a constraint. However, solving this constrained optimal control problem for general nonlinear systems remains challenging. In this work, we use the general framework of constrained optimal control, but given the safety state constraint, we convert it into an equivalent control constraint, resulting in a state and time-dependent control-constrained optimal control problem. This equivalent optimal control problem can readily be solved using the dynamic programming principle. We show the corresponding value function is a viscosity solution of a certain Hamilton-Jacobi-Bellman Partial Differential Equation (HJB-PDE). Furthermore, we demonstrate the effectiveness of our method with a two-dimensional case study, and the experiment shows that the controller synthesized using our method consistently outperforms the baselines, both in safety and performance.
format Preprint
id arxiv_https___arxiv_org_abs_2409_06696
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Cooptimizing Safety and Performance with a Control-Constrained Formulation
Wang, Hao
Dhande, Adityaya
Bansal, Somil
Systems and Control
Robotics
Autonomous systems have witnessed a rapid increase in their capabilities, but it remains a challenge for them to perform tasks both effectively and safely. The fact that performance and safety can sometimes be competing objectives renders the cooptimization between them difficult. One school of thought is to treat this cooptimization as a constrained optimal control problem with a performance-oriented objective function and safety as a constraint. However, solving this constrained optimal control problem for general nonlinear systems remains challenging. In this work, we use the general framework of constrained optimal control, but given the safety state constraint, we convert it into an equivalent control constraint, resulting in a state and time-dependent control-constrained optimal control problem. This equivalent optimal control problem can readily be solved using the dynamic programming principle. We show the corresponding value function is a viscosity solution of a certain Hamilton-Jacobi-Bellman Partial Differential Equation (HJB-PDE). Furthermore, we demonstrate the effectiveness of our method with a two-dimensional case study, and the experiment shows that the controller synthesized using our method consistently outperforms the baselines, both in safety and performance.
title Cooptimizing Safety and Performance with a Control-Constrained Formulation
topic Systems and Control
Robotics
url https://arxiv.org/abs/2409.06696