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  5. Adaptive-Critic Design for Decentralized Event-Triggered Control of Constrained Nonlinear Interconnected Systems Within an Identifier-Critic Framework

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Article
English
2021

Adaptive-Critic Design for Decentralized Event-Triggered Control of Constrained Nonlinear Interconnected Systems Within an Identifier-Critic Framework

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English
2021
IEEE Transactions on Cybernetics
Vol 52 (8)
DOI: 10.1109/tcyb.2020.3037321

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Hamid Reza Karimi
Hamid Reza Karimi

Politecnico di Milano

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Xin Huo
Hamid Reza Karimi
Xudong Zhao
+2 more

Abstract

This article studies the decentralized event-triggered control problem for a class of constrained nonlinear interconnected systems. By assigning a specific cost function for each constrained auxiliary subsystem, the original control problem is equivalently transformed into finding a series of optimal control policies updating in an aperiodic manner, and these optimal event-triggered control laws together constitute the desired decentralized controller. It is strictly proven that the system under consideration is stable in the sense of uniformly ultimate boundedness provided by the solutions of event-triggered Hamilton-Jacobi-Bellman equations. Different from the traditional adaptive critic design methods, we present an identifier-critic network architecture to relax the restrictions posed on the system dynamics, and the actor network commonly used to approximate the optimal control law is circumvented. The weights in the critic network are tuned on the basis of the gradient descent approach as well as the historical data, such that the persistence of excitation condition is no longer needed. The validity of our control scheme is demonstrated through a simulation example.

How to cite this publication

Xin Huo, Hamid Reza Karimi, Xudong Zhao, Bohui Wang, Guangdeng Zong (2021). Adaptive-Critic Design for Decentralized Event-Triggered Control of Constrained Nonlinear Interconnected Systems Within an Identifier-Critic Framework. IEEE Transactions on Cybernetics, 52(8), pp. 7478-7491, DOI: 10.1109/tcyb.2020.3037321.

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Publication Details

Type

Article

Year

2021

Authors

5

Datasets

0

Total Files

0

Language

English

Journal

IEEE Transactions on Cybernetics

DOI

10.1109/tcyb.2020.3037321

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