Adaptive dynamic programming for decentralized neuro‐control of nonlinear systems subject to mismatched interconnections

This article presents a decentralized neuro‐control scheme for a class of continuous‐time nonlinear systems with mismatched interconnections through an optimal control method. The decentralized control problem of the studied nonlinear‐interconnected systems is transformed into a group of optimal con...

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Vydáno v:Optimal control applications & methods Ročník 43; číslo 5; s. 1501 - 1519
Hlavní autoři: Tang, Yuhong, Yang, Xiong, Dong, Na
Médium: Journal Article
Jazyk:angličtina
Vydáno: Glasgow Wiley Subscription Services, Inc 01.09.2022
Témata:
Adaptive algorithms
Adaptive control
adaptive dynamic programming
Control methods
Decentralized control
Dynamic programming
Interconnections
mismatched interconnection
Neural networks
Nonlinear control
Nonlinear systems
Optimal control
Policies
reinforcement learning
Subsystems
ISSN:0143-2087, 1099-1514
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Shrnutí:This article presents a decentralized neuro‐control scheme for a class of continuous‐time nonlinear systems with mismatched interconnections through an optimal control method. The decentralized control problem of the studied nonlinear‐interconnected systems is transformed into a group of optimal control problems of auxiliary subsystems. First, the value functions of auxiliary subsystems are designed, which are related to the boundaries of interconnected terms. It is proved that, under certain conditions, the decentralized control consisting of optimal control policies of auxiliary subsystems can stabilize the entire interconnected system. Then, an adaptive dynamic programming algorithm is presented to solve the Hamilton–Jacobi–Bellman equations. Critic neural networks (NNs) are employed to approximate the value functions of auxiliary subsystems in order to acquire the optimal control policies. Moreover, the auxiliary subsystems' states and the critic NNs' weight estimation errors are proved to be uniformly ultimately bounded. Finally, a numerical example and an interconnected power system are provided to validate the proposed decentralized neuro‐control strategy.
Bibliografie:Funding information
National Natural Science Foundation of China, Grant/Award Number: 61973228
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SourceType-Scholarly Journals-1
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ISSN:0143-2087
1099-1514
DOI:10.1002/oca.2905