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An event‐triggered integer‐mixed adaptive dynamic programming for switched nonlinear systems with bounded inputs
Author(s) -
Han Xiumei,
Qin Haiqin,
Wang Zhitao,
Xu Ning,
Zhao Xudong,
Zhao Jinfeng
Publication year - 2021
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.5668
Subject(s) - control theory (sociology) , dynamic programming , integer (computer science) , bounded function , bellman equation , nonlinear system , computer science , sequence (biology) , function (biology) , optimal control , mathematical optimization , integer programming , mathematics , control (management) , mathematical analysis , physics , quantum mechanics , artificial intelligence , evolutionary biology , biology , genetics , programming language
This paper studies the optimal event‐triggered control for constrained‐input discrete‐time switched nonlinear systems. Firstly, the optimal time‐triggered control problem is analyzed based on the necessary optimality condition. Secondly, the optimal event‐triggered control problem is presented, and the optimal results are presented based on the periodic time‐triggered ones, and an event‐triggered integer‐mixed adaptive dynamic programming algorithm is put forward to obtain the optimal results. The proposed algorithm is only executed at trigger instants, which decreases the execution times compared with the periodic time‐triggered algorithm, and the neural networks are applied to approximate the control input and costate vector functions of each subsystem based on the triggered states. Thirdly, an event‐triggered condition is designed to make the closed‐loop switched system asymptotically stable. Fourthly, it is shown that during the iteration process, the value function sequence corresponding to the costate vector converges to the optimal value function. Finally, the simulation results demonstrate the effectiveness of the presented algorithm.