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Main Authors: Zhou, Mi, Verriest, Erik, Abdallah, Chaouki
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2409.10722
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author Zhou, Mi
Verriest, Erik
Abdallah, Chaouki
author_facet Zhou, Mi
Verriest, Erik
Abdallah, Chaouki
contents Model-free algorithms are brought into the control system's research with the emergence of reinforcement learning algorithms. However, there are two practical challenges of reinforcement learning-based methods. First, learning by interacting with the environment is highly complex. Second, constraints on the states (boundary conditions) require additional care since the state trajectory is implicitly defined from the inputs and system dynamics. To address these problems, this paper proposes a new model-free algorithm based on basis functions, gradient estimation, and the Lagrange method. The favorable performance of the proposed algorithm is shown using several examples under state-dependent switches and time delays.
format Preprint
id arxiv_https___arxiv_org_abs_2409_10722
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Model-Free Optimal Control Method With Fixed Terminal States and Delay
Zhou, Mi
Verriest, Erik
Abdallah, Chaouki
Systems and Control
Model-free algorithms are brought into the control system's research with the emergence of reinforcement learning algorithms. However, there are two practical challenges of reinforcement learning-based methods. First, learning by interacting with the environment is highly complex. Second, constraints on the states (boundary conditions) require additional care since the state trajectory is implicitly defined from the inputs and system dynamics. To address these problems, this paper proposes a new model-free algorithm based on basis functions, gradient estimation, and the Lagrange method. The favorable performance of the proposed algorithm is shown using several examples under state-dependent switches and time delays.
title A Model-Free Optimal Control Method With Fixed Terminal States and Delay
topic Systems and Control
url https://arxiv.org/abs/2409.10722