Adaptive Fuzzy Sampling Control For Uncertain Nonlinear System

In this paper,for several typical uncertain nonlinear systems,the control design problem of periodic sampling and event-triggered based nonuniform periodic sampling are studied by introducing the related technologies.By combing fuzzy logic systems and sampling control theory,and by considering Backstepping algorithm,the design method of fuzzy adaptive periodic sampling controller and fuzzy adaptive nonuniform periodic sampling controller are proposed respectively.The stability and feasibility of the controlled plant are verified by Lyapunov theory.The main works of this paper are as follows:For a class of nonlinear systems with transmission delay and time-varying input delay,under the framework of Backstepping design method,a fuzzy estimation model is introduced through the fuzzy logic system and adaptive control technology.By using the information of the fuzzy estimation model to replace the sampling information of the original system,a periodic sampling controller is designed.Finally,Lyapunov theory is used to prove that the proposed adaptive fuzzy periodic sampling control strategy can guarantee the stability of the controlled system.The nonuniform periodic sampling control problem for a class of nonlinear systems with unknown dead zone is studied.In this method,the event trigger mechanism is used to determine whether the system information needs to be sampled or not,and the nonuniform periodic sampling information is used to constituent the sampling controller.Under the framework of adaptive Backstepping technology,an adaptive fuzzy control strategy is proposed by considering the prescribed performance method and dynamic surface technique,which can effectively guarantee the control effect of the nonuniform periodic sampling controller and avoid the "explosion of complexity" issue.Combined with Lyapunov theory,the reliability of the design algorithm is verified.In the design process,the event triggering mechanism is designed to avoid Zeno behavior.Moreover,based on the theory of prescribed performance,this method not only ensures that the tracking error and state approximation error could reach the stabilization,but also guarantees that the tracking error was always limited to the specified limit.For a class of nonlinear interconnected large scale systems,the problem of adaptive fuzzy decentralized periodic sampling control design is studied by designing a nonlinear fuzzy sampling observer.Under the framework of Backstepping algorithm,a corresponding adaptive fuzzy decentralized control scheme is designed by using periodic sampling control method and adaptive fuzzy decentralized control theory.In the design process of the controller,the dynamic surface control technology is considered to avoid the problem of "explosion of complexity",which exists in the framework of Backstepping.According to Granwall inequality and Lyapunov stability theory,it is proved that the proposed output feedback periodic control strategy can guarantee the stability of the closed-loop system.The decentralized nonuniform periodic control problem for a class of interconnected large nonlinear systems with time delay is considered.In the design process,the mixed event triggering mechanism based on the state signal was designed to determine whether the system state information needs to be sampled.Combined with Backstepping technology framework,the adaptive law and virtual controller are designed.By using the dynamic surface technology based on nonlinear filter,an event-triggered control dynamic surface design strategy is proposed,which can effectively avoid the problem of "problem of explosion" under the framework of Backstepping technology.The effectiveness of the proposed algorithm is verified according to Lyapunov theory.This method not only ensures that the tracking error can reach the stabilization,but also avoids Zeno behavior of the mixed event triggering mechanism.