A new Lyapunov functional approach to sampled-data synchronization control for delayed neural networks |
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Authors: | Shen-Ping Xiao Hong-Hai Lian Kok Lay Teo Hong-Bing Zeng Xiao-Hu Zhang |
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Institution: | 1. School of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China;2. Key Laboratory for Electric Drive Control and Intelligent Equipment of Hunan Province, Zhuzhou 412007, China;3. School of Wind Energy Engineering, Hunan Electrical College of Technology, Xiangtan 411101, China;4. Coordinated Innovation Center for Computable Modeling in Management Science, Tianjin University of Finance and Economics, Tianjin 300222, China;5. Department of Mathematics and Statistics, Curtin University, Perth, WA 6102, Australia |
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Abstract: | This paper discusses the problem of synchronization for delayed neural networks using sampled-data control. We introduce a new Lyapunov functional, called complete sampling-interval-dependent discontinuous Lyapunov functional, which can adequately capture sampling information on both intervals from to and from to . Based on this Lyapunov functional and an improved integral inequality, less conservative conditions are derived to ensure the stability of the synchronization error system, leading to the fact that the drive neural network is synchronized with the response neural network. The desired sampled-data controller is designed in terms of solutions to linear matrix inequalities. A numerical example is provided to demonstrate that the proposed approaches are effective and superior to some existing ones in the literature. |
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Keywords: | Corresponding author at: School of Electrical and Information Engineering Hunan University of Technology Zhuzhou 412007 China |
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