具有未知动态和噪声测量的连续时间对称系统的优化控制

arXiv - CS - Systems and Control Pub Date : 2024-03-20 DOI:arxiv-2403.13605

Hamed Taghavian, Florian Dorfler, Mikael Johansson

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引用次数: 0

摘要

针对系统具有未知动态的外部对称性的连续时间线性二次最优控制问题，提出了一种迭代学习算法。有限视距和无限视距问题均在考虑之列。结果表明，所提出的算法在全局上收敛于最优解，与自适应动态编程相比具有一些优势，包括在噪声测量条件下无偏，计算负担相对较低。数值实验显示了结果的有效性。

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Optimal control of continuous-time symmetric systems with unknown dynamics and noisy measurements

An iterative learning algorithm is presented for continuous-time linear-quadratic optimal control problems where the system is externally symmetric with unknown dynamics. Both finite-horizon and infinite-horizon problems are considered. It is shown that the proposed algorithm is globally convergent to the optimal solution and has some advantages over adaptive dynamic programming, including being unbiased under noisy measurements and having a relatively low computational burden. Numerical experiments show the effectiveness of the results.

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arXiv - CS - Systems and Control

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