Event-triggered adaptive NN practical finite-time control with its application to MPCVD reactors |
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| Institution: | 1. College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China;2. Ningbo Institute of Intelligent Equipment Technology Co., Ltd, Ningbo 315201, China;3. Research Institute of Intelligent Control and Systems, School of Astronautics, Harbin Institute of Technology, Harbin 150001, China;1. Department of Applied Mathematics, School of Science, Dalian Maritime University, Dalian 116026, PR China;2. College of Transportation Engineering, Dalian Maritime University, Dalian, Liaoning 116026, PR China;3. School of Management, Guangzhou University, Guangzhou, 510006, PR China;4. School of Mathematics and Information Science, Shandong Institute of Business and Technology, Yantai 264005, PR China;5. School of Mathematical Sciences, Sunway University, Bandar Sunway, Selangor Darul Ehsan 47500, Malaysia;6. Teaching and Research Office of Mathematics, Department of Basics, PLA Dalian Naval Academy, Dalian, Liaoning 116018, PR China |
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| Abstract: | The practical finite-time control problem of uncertain nonlinear systems is investigated in this paper. To address the uncertain nonlinearities of the system, neural networks are introduced to approximate the lumped nonlinearities containing the system unknown functions. On the other hand, to alleviate the signal transmission pressure of the system, an improved event-triggered mechanism is presented to reduce the controller update frequency without degrading the control performance of the system. By using practical finite-time stability, it is obtained that the system tracking errors are practical finite-time stable without Zeno behavior. Finally, the effectiveness of the proposed method is verified by the simulation results of its application to a microwave plasma chemical vapor deposition (MPCVD) reactor system. |
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