Adaptive Event-triggered Controland Filter For T-S Fuzzy Systems

Recently,netwoked control systems(NCSs)have been widely investigated in T-S fuzzy model.Due to that T-S fuzzy model can approximate any continuous function by a series of the IF-THEN rules,so that many traditional methods of linear system are available for its research and it is an important tool for researching nonlinear system.In order to reduce the limited network resource,event-triggered scheme has been widely used in NCSs,which is important in theoretical development.However,it is worth noting that the results obtained for event-triggered NCSs are still very limited: firstly,in the obtained event-triggered scheme,network bandwidth resource is considered instead of the shortcomings that if the message is too little,it will degrade the performance of control system.This shows that reducing network bandwidth while maintaining control performance is about balance.Based on this idea,the adaptive event-triggered scheme is proposed in some researchs;Secondly,the current research about event-triggered scheme for T-S fuzzy system is not yet mature.Therefore,to design controller and filter with adaptive event-triggered scheme is especially important.The content of this paper can be summarized as follows:1?In this paper,adaptive event-triggered scheme has been proposed based on event-triggered scheme,which is applied to the design of controller and filter respectively.The key of adaptive event-triggered scheme is to find an optimal threshold instead of a pre-given threshold.In this paper,a defined differential equation can determine the trigger parameter ?(t),of which the parameter d is dynamic.2?Based on T-S fuzzy systems with time delay,new design plans for adaptive event-triggered controller and H_? filter have been investigated.A new Lyapunov-Krasovskii functional and some slack matrices are used in the proof of main results.Schur lemma etc.are used to deal with nonlinear matrix inequality,then the ideal controller and filter are designed by solving linear matrix inequality(LMI).Finally,the simulation examples verify the validity of the proposed design plans.