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Bibliographic Details
Main Authors: Kounatidis, Panagiotis, Malikopoulos, Andreas A.
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2603.27677
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author Kounatidis, Panagiotis
Malikopoulos, Andreas A.
author_facet Kounatidis, Panagiotis
Malikopoulos, Andreas A.
contents In this paper, we present a framework for solving continuous optimal control problems when the true system dynamics are approximated through an imperfect model. We derive a control strategy by applying Pontryagin's Minimum Principle to the model-based Hamiltonian functional, which includes an additional penalty term that captures the deviation between the model and the true system. We then derive conditions under which this model-based strategy coincides with the optimal control strategy for the true system under mild convexity assumptions. We demonstrate the framework on a real robotic testbed for the cruise control application with safety distance constraints.
format Preprint
id arxiv_https___arxiv_org_abs_2603_27677
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Safety-Constrained Optimal Control for Unknown System Dynamics
Kounatidis, Panagiotis
Malikopoulos, Andreas A.
Systems and Control
In this paper, we present a framework for solving continuous optimal control problems when the true system dynamics are approximated through an imperfect model. We derive a control strategy by applying Pontryagin's Minimum Principle to the model-based Hamiltonian functional, which includes an additional penalty term that captures the deviation between the model and the true system. We then derive conditions under which this model-based strategy coincides with the optimal control strategy for the true system under mild convexity assumptions. We demonstrate the framework on a real robotic testbed for the cruise control application with safety distance constraints.
title Safety-Constrained Optimal Control for Unknown System Dynamics
topic Systems and Control
url https://arxiv.org/abs/2603.27677