Joint Chance Constrained Optimal Control via Linear Programming
Optimization and Control
2024-05-21 v2 Systems and Control
Systems and Control
Abstract
We establish a linear programming formulation for the solution of joint chance constrained optimal control problems over finite time horizons. The joint chance constraint may represent an invariance, reachability or reach-avoid specification that the trajectory must satisfy with a predefined probability. For finite state and action spaces, the solution is exact and our method computationally superior to approaches in the literature. For continuous state or action spaces, our linear programming formulation enables basis function approximations.
Cite
@article{arxiv.2402.19360,
title = {Joint Chance Constrained Optimal Control via Linear Programming},
author = {Niklas Schmid and Marta Fochesato and Tobias Sutter and John Lygeros},
journal= {arXiv preprint arXiv:2402.19360},
year = {2024}
}