Event-triggered adaptive neural control for state-constrained switched nonlinear systems based on nonlinear shifting function technique |
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| Institution: | 1. School of Mathematics Science, Liaocheng University, Liaocheng 252000, China;2. School of Mathematics, University of Manchester, Manchester M13 9PL, UK;3. School of Electrical and Information Engineering, Anhui University of Technology, Maanshan 243002, China;1. School of Information Engineering, Henan University of Science and Technology, Luoyang 471023, P.R. China;2. Department of Automatic Control, Robotics and Fluid Technique, Faculty of Mechanical and Civil Engineering, University of Kragujevac, 36000 Kraljevo, Serbia;1. MOE-LCSM, CHP-LCOCS, School of Mathematical Sciences and Statistics, Hunan Normal Univerity, Changsha, 410081, China;2. The Key Laboratory of Control and Optimization of Complex Systems, College of Hunan Province, Hunan Normal University, Changsha 410081, China;1. School of Engineering, Qufu Normal University, Rizhao, 276800, China;2. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, 200444, China;1. Marine Electrical Engineering College, Dalian Maritime University, Dalian, Liaoning 116026, China;2. College of Science, Liaoning University of Technology, Jinzhou, Liaoning 121001, China;3. School of Navigation, Dalian Maritime University, Dalian, Liaoning 116026, China;1. College of Science, Guilin University of Technology, Guilin, Guangxi 541004, PR China;2. School of Mathematics and Statistics, Guangxi Normal University, Guilin, Guangxi 541006, PR China;3. College of Electronic and Information Engineering, Southwest University, Chongqing 400715, PR China;4. School of Information Science and Engineering, Chengdu University, Chengdu, Sichuan 610106, PR China |
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| Abstract: | This paper addresses the event-triggered tracking control design for state-constrained switched nonstrict feedback nonlinear systems. With the help of a time-varying nonlinear shifting function (TVNSF) introduced into the switched nonlinear system, the proposed solution is seen as a unified tool regardless of whether the constraint conditions are state constraints, output constraint, or even no constraint. Also, by allowing the triggering error to vary with the switching signal in time, the negative effects of the mismatch between the individual controller and the subsystem on system performance are trumped. Moreover, by using constructed individual Lyapunov function that depends on the lower bound of the control gain function of individual subsystem, a novel switching signal satisfying the average dwell time (ADT) is provided to ensure the boundedness of all variables in the closed-loop system. Finally, the proposed theory is carried over into a mass-spring-damper system to verify its effectiveness. |
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