Hybrid anti-bump control for switched nonlinear systems with event-triggering under sampled-data-based switching |
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| Institution: | 1. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China;2. Key Laboratory of Data Analytics and Optimization for Smart Industry, Northeastern University, Ministry of Education, China;3. College of Information Science and Engineering, Northeastern University, Shenyang 110819, China;1. School of Computer Science and Engineering, Hunan University of Science and Technology, China;2. Department of Sports Medicine and Joint Surgery, Nanjing First Hospital, Nanjing Medical University, China;3. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;4. College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, China;1. Center for Control Theory and Guidance Technology, Harbin Institute of Technology, Harbin 150001, China;2. Center for Control Science and Technology, Southern University of Science and Technology, Shenzhen 518055, China |
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| Abstract: | This paper addresses the hybrid anti-bump control for switched nonlinear systems with event-triggering via the interval type-2 (IT2) fuzzy model. A unified framework of anti-bump performance for switched nonlinear systems called hybrid anti-bump performance is established to attenuate sudden big hybrid bumps caused by both triggering and switching. Then, we design a sampled-data-based switching strategy, under which we only need to check the switching conditions at discrete sampling instants. By using the multiple Lyapunov–Krasovskii functional theory and the constructed switching law, sufficient conditions are made for the considered systems to be asymptotically stable with both performance and hybrid anti-bump performance. Moreover, the switching law, the event-triggered scheme, and the event-triggered controllers are jointly designed. Finally, an electro-hydraulic model is exploited to verify the applicability and effectiveness of our method. |
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