Verification of Autonomous Systems with Optimal Controllers

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Le, Dylan, McCandless, Joel, Varela, Carlos, Ivanov, Radoslav
Format: Preprint
Published: 2026
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866913040778133504
author Le, Dylan
McCandless, Joel
Varela, Carlos
Ivanov, Radoslav
author_facet Le, Dylan
McCandless, Joel
Varela, Carlos
Ivanov, Radoslav
contents This paper considers the problem of reachability analysis of control systems with optimal controllers, as a first step towards verifying the safety and correctness of such systems. Despite their appeal in guaranteeing task satisfaction through cost minimization, optimal controllers are often challenging to assure. In particular, as system dynamics grow in complexity, solving the resulting optimization problem may be difficult, especially given time and computation constraints on real platforms. Thus, it is essential to verify that, even if the optimal solution is not always found, such controllers still accomplish the high-level control objective. In this paper, we focus on gradient descent algorithms and design a reachability algorithm by treating gradient descent as a separate (digital) dynamical system, embedded in the original (physical) dynamical system, with controls as part of the state. We evaluate the feasibility of the proposed method on two control systems, a two-dimensional quadrotor and a cartpole.
format Preprint
id arxiv_https___arxiv_org_abs_2604_15659
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Verification of Autonomous Systems with Optimal Controllers
Le, Dylan
McCandless, Joel
Varela, Carlos
Ivanov, Radoslav
Systems and Control
This paper considers the problem of reachability analysis of control systems with optimal controllers, as a first step towards verifying the safety and correctness of such systems. Despite their appeal in guaranteeing task satisfaction through cost minimization, optimal controllers are often challenging to assure. In particular, as system dynamics grow in complexity, solving the resulting optimization problem may be difficult, especially given time and computation constraints on real platforms. Thus, it is essential to verify that, even if the optimal solution is not always found, such controllers still accomplish the high-level control objective. In this paper, we focus on gradient descent algorithms and design a reachability algorithm by treating gradient descent as a separate (digital) dynamical system, embedded in the original (physical) dynamical system, with controls as part of the state. We evaluate the feasibility of the proposed method on two control systems, a two-dimensional quadrotor and a cartpole.
title Verification of Autonomous Systems with Optimal Controllers
topic Systems and Control
url https://arxiv.org/abs/2604.15659