Data‐driven adaptive optimal control for discrete‐time periodic systems

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Hauptverfasser: Ai‐Guo Wu, Yuan Meng
Format: Artículo Open Access
Veröffentlicht: Wiley 2024
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author Ai‐Guo Wu
Yuan Meng
author_facet Ai‐Guo Wu
Yuan Meng
Ai‐Guo Wu
Yuan Meng
collection Wiley Open Access
contents Data‐driven adaptive optimal control for discrete‐time periodic systems Ai‐Guo Wu Yuan Meng International Journal of Robust and Nonlinear Control AbstractIn this paper, a problem of data‐driven optimal control is studied for discrete‐time periodic systems with unknown system matrices and input matrices. For this problem, a value iteration‐based adaptive dynamic programming algorithm is proposed to obtain the suboptimal controller. The core of the algorithm proposed in this paper is to obtain an approximation of the unique positive definite solution of the algebraic Riccati equation and the optimal feedback gain matrix by using the collected real‐time data of the system states and control inputs. Without an initial stabilizing feedback gain, the proposed algorithm could be activated by an arbitrary bounded control input. Finally, the effectiveness of the proposed approach is demonstrated by two examples. 10.1002/rnc.7421 http://onlinelibrary.wiley.com/termsAndConditions#vor
doi_str_mv 10.1002/rnc.7421
format Artículo Open Access
id wiley_oa_10_1002_rnc_7421
institution Wiley Open Access
license_str_mv http://onlinelibrary.wiley.com/termsAndConditions#vor
publishDate 2024
publisher Wiley
record_format wiley_oa
spellingShingle Data‐driven adaptive optimal control for discrete‐time periodic systems
Ai‐Guo Wu
Yuan Meng
International Journal of Robust and Nonlinear Control
Data‐driven adaptive optimal control for discrete‐time periodic systems Ai‐Guo Wu Yuan Meng International Journal of Robust and Nonlinear Control AbstractIn this paper, a problem of data‐driven optimal control is studied for discrete‐time periodic systems with unknown system matrices and input matrices. For this problem, a value iteration‐based adaptive dynamic programming algorithm is proposed to obtain the suboptimal controller. The core of the algorithm proposed in this paper is to obtain an approximation of the unique positive definite solution of the algebraic Riccati equation and the optimal feedback gain matrix by using the collected real‐time data of the system states and control inputs. Without an initial stabilizing feedback gain, the proposed algorithm could be activated by an arbitrary bounded control input. Finally, the effectiveness of the proposed approach is demonstrated by two examples. 10.1002/rnc.7421 http://onlinelibrary.wiley.com/termsAndConditions#vor
title Data‐driven adaptive optimal control for discrete‐time periodic systems
topic International Journal of Robust and Nonlinear Control
url https://onlinelibrary.wiley.com/doi/10.1002/rnc.7421