Study On Event-triggered Filtering For Discrete Fuzzy Systems

In recent years,the development of computer,com munication and control technology has changed rapidly.Researchers have carried out a lot of research on networked control systems,and have obtained a wealth of research results,including the design of controllers,state estimators,and filters for networked control systems.While the network control system is widely used,it also faces many problems.On the one hand,due to the non-linear factors in a large number of physical processes and the complex principles,it is difficult to obtain accurate mathematical models.The T-S fuzzy model has the excellent characteristic of dealing with non-linear problems.It can approximate smooth non-linear functions with arbitrary accuracy through the combination of some linear systems.Therefore,whether it is the research on the stability of the network control system or the filtering problem,the T-S fuzzy model has great theoretical significance and practical value.On the other hand,traditional control systems use periodic triggering to transmit data.For networks,this triggering method consumes more bandwidth resources.Due to the limited network bandwidth,when a large amount of data is transmitted,it will cause data transmission delay.To solve this problem,scholars have proposed an event-triggered mechanism to filter useless data,thereby reducing the network transmission burden.However,the current research on discrete fuzzy systems based on event triggering mechanism under network needs further exploration.Based on this,this paper starts from the state estimation and filtering problems of discrete fuzzy systems,and considers the network transmission delay,and under the consideration of event-triggered mechanism,designs a state estimator and filter for discrete T-S fuzzy systems using the stability analysis theory of nonlinear systems.The main research is as follows:1.Aiming at the estimation problem of event-triggered mechanism in discrete T-S fuzzy system,a comprehensive stability analysis is carried out.In the stability analysis,some integral inequality scaling processes are introduced to solve the time delay problem,and the theorem conditions for the asymptotic stability of the system and the feasible solution of the state estimator are obtained.The parameters are obtained by linear matrix inequality technology.A numerical simulation example is given to verify the effectiveness of the method.2.For discrete fuzzy systems,a system model is established by introducing a similar event-triggered mechanism and further considering the influence of the disturbance amount on the output result.By introducing performance indicators,the conditions for asymptotic stability of the system and the existence of a feasible solution for the filter are obtained,and a simulation example is given to verify the effectiveness of the method.