Adaptive Dynamic Programming for Optimal Control of Discrete-Time Nonlinear Systems With Trajectory-Based Initial Control Policy

The policy gradient adaptive dynamic programming (PGADP) technique has gained recognition as an effective approach for optimizing the performance of nonlinear systems. Nonetheless, existing PGADP algorithms often demand a substantial volume of expensive or potentially risky interaction data with the...

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Bibliographic Details
Published in:	IEEE transactions on systems, man, and cybernetics. Systems Vol. 54; no. 3; pp. 1489 - 1501
Main Authors:	Xu, Jiahui, Wang, Jingcheng, Rao, Jun, Wu, Shunyu, Zhong, Yanjiu
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.03.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Adaptive control Adaptive dynamic programming (ADP) Algorithms Closed loops Controllers Discrete time systems Dynamic programming Feedback control Heuristic algorithms initial control policy Neural networks Nonlinear control Nonlinear systems Optimal control Optimization OptNet Predictive control System dynamics System effectiveness Training Trajectory Trajectory control
ISSN:	2168-2216, 2168-2232
Online Access:	Get full text
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