Event-triggered adaptive NN control for MIMO switched nonlinear systems with non-ISpS unmodeled dynamics |
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| Institution: | 1. College of Information Science and Engineering, Northeastern University, Shenyang, 110819, China;2. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, 110819, China;1. School of Computer Science and Technology, Huaiyin Normal University, Huaian 223300, Jiangsu, China;2. School of Mathematics, Southeast University, Nanjing 210096, China;3. Yonsei Frontier Lab, Yonsei University, Seoul 03722, South Korea;4. School of Mathematical Science, Huaiyin Normal University, Huaian 223300, Jiangsu, China;1. AnHui Province Key Laboratory of Special Heavy Load Robot, Anhui University of Technology, Ma’anshan 243002, PR China;2. School of Automation and Electrical Engineering, Linyi University, Linyi 276005, PR China;3. School of Information Science and Engineering, Chengdu University, Chengdu 610106, PR China;1. Tecnológico Nacional de México, Instituto Tecnológico de La Paz, La Paz, B.C.S., México;2. Centro de Investigación Científica y de Educación Superior de Ensenada, Ensenada, B.C., México;3. Tecnológico Nacional de México, Instituto Tecnológico de La Laguna, Torreón, Coahuila, México;1. School of Electrical Engineering, Zhengzhou University, Zhengzhou, 450001, China;2. Guangdong Discrete Manufacturing Knowledge Automation Engineering Technology Research Center, School of Automation, Guangdong University of Technology, Guangzhou, 510006, China;3. Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing, School of Automation, Guangdong University of Technology, Guangzhou, 510006, China |
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| Abstract: | This paper investigates the problem of event-triggered adaptive neural network (NN) control for multi-input multi-output (MIMO) switched nonlinear systems with output and state constraints and non-input-to-state practically stable (ISpS) unmodeled dynamics. A nonlinear mapping is firstly utilized to deal with output and state constraints. Also, by developing a new switching signal with persistent dwell-time (PDT) and a switching dependent dynamic signal, the difficulty caused by some non-ISpS unmodeled dynamics is overcome. Then, a type of switching event-triggering mechanisms (ETMs) and event-triggered adaptive NN controllers of subsystems are designed, which handle the issue of asynchronous switching without requiring any known restriction on maximum asynchronous time. A piecewise constant introduced into this ETM effectively ensures a strict positive lower bound of inter-event times. Zeno behavior is thus ruled out. Finally, by proposing a novel class of switching signals with reset PDT, it is ensured that all output and state constrains are never violated and all signals of the switched closed-loop system are semi-global uniform ultimate boundedness (SGUUB). A two inverted pendulum system and a numerical example are provided for illustrating the applicability and validity of the proposed method. |
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