Verification of Autonomous Systems with Optimal Controllers
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866913040778133504 |
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| 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 |