Twin Deterministic Policy Gradient Adaptive Dynamic Programming for Optimal Control of Affine Nonlinear Discrete-time Systems

Recent achievements in the field of adaptive dynamic programming (ADP), as well as the data resources and computational capabilities in modern control systems, have led to a growing interest in learning and data-driven control technologies. This paper proposes a twin deterministic policy gradient ad...

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Veröffentlicht in:	International journal of control, automation, and systems Jg. 20; H. 9; S. 3098 - 3109
Hauptverfasser:	Xu, Jiahui, Wang, Jingcheng, Rao, Jun, Zhong, Yanjiu, Zhao, Shangwei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Bucheon / Seoul Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers 01.09.2022 Springer Nature B.V 제어·로봇·시스템학회
Schlagworte:	Adaptive control Algorithms Control Discrete time systems Dynamic programming Engineering Liapunov functions Machine learning Mechatronics Nonlinear control Nonlinear systems Optimal control Regular Paper Robotics 제어계측공학 optimal control affine nonlinear system twin deterministic policy gradient Adaptive dynamic programming
ISSN:	1598-6446, 2005-4092
Online-Zugang:	Volltext
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