Event-triggered gain-scheduling dissipative synchronization control for switched neural networks under state-dependent switching |
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| Institution: | 1. AnHui Province Key Laboratory of Special Heavy Load Robot and School of Electrical and Information Engineering, Anhui University of Technology, Ma’anshan 243002, China;2. College of Intelligent Science and Control Engineering, Jinling Institute of Technology, Nanjing, Jiangshu 211169, China;1. Science and Technology on Aircraft Control Laboratory, School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China;2. Peng Cheng Laboratory, Shenzhen 518000, China;1. College of Information Science and Engineering, Northeastern University, Shenyang 110819, PR China;2. State Key Laboratory of Synthetical Automation for Process Industries (Northeastern University), Shenyang 110819, PR China |
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| Abstract: | The dissipative synchronization problem of delayed Markov jump switched neural networks (MJSNNs) under state-dependent switching by the event-triggered gain-scheduling control scheme is studied in this paper. By the introduction of a Markov jump model, which is used to depict the random variation wherein the connection of MJSNNs, the issues we study can take more generality. Via constructing suitable Lyapunov–Krasovskii functionals (LKFs) and applying some matrix inequality scaling methods, sufficient conditions for dissipative synchronization of delayed MJSNN are established. According to such criteria, the event-triggered gain-scheduling control scheme is adopted to design a controller with less terminal communication costs. Finally, a numerical example is given to demonstrate the effectiveness of the proposed method. |
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