NDLI: Optimal control of unknown discrete-time nonlinear systems with constrained inputs using GDHP technique

Content Provider	IEEE Xplore Digital Library
Author	Liu Derong Wang Ding Li Hongliang
Copyright Year	2012
Description	Author affiliation: State Key Laboratory of Management and Control for Complex Systems Institute of Automation, Chinese Academy of Sciences, Beijing 100190, P.R. China (Liu Derong; Wang Ding; Li Hongliang)
Abstract	The adaptive dynamic programming (ADP) approach is employed to design an optimal controller for unknown discrete-time nonlinear systems with control constraints. First, a neural network is constructed to identify the unknown dynamical system with stability proof. Then, the iterative ADP algorithm is developed to solve the optimal control problem with convergence analysis. Moreover, two other neural networks are introduced to approximate the cost function and its derivative and the control law, under the framework of globalized dual heuristic programming technique. Finally, two simulation examples are included to verify the theoretical results.
Starting Page	2926
Ending Page	2931
File Size	265124
Page Count	6
File Format	PDF
ISBN	9781467325813
ISSN	21612927
e-ISBN	9789881563811
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Chinese Assoc of Automati
Subject Keyword	Adaptive dynamic programming Neural networks Control constraints Optimal control Approximate dynamic programming System identification
Content Type	Text
Resource Type	Article

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Optimal control of unknown discrete-time nonlinear systems with constrained inputs using GDHP technique