Research On Synthesis And Fault Diagnosis For T-S Fuzzy Control Systems Based On Event-triggered Mechanism

Networked control systems have been widely utilized in aerospace industry,medical treatment and intelligent transportation due to the advantages of low cost,easy maintenance,share of information resources and so on.However,due to the limitations of signal transmission rates and network bandwidths,network-induced delays and data packet dropouts are also introduced in the data transmission via network of the sampled data.In order to reduce the occurrence of these problems,event-triggered control method is a hot research area of scholars at home and abroad in recent years.It can be used to reduce the frequency of data transmission.Although many valuable achievements have been published in the theoretical research of fuzzy networked control systems based on event-triggered mechanism,there are still many important scientific problems to be solved in the research of synthesis and fault diagnosis of fuzzy networked control systems with uncertain parameters in the actual system modeling.On the basis of the previous works,this dissertation studies some problems for fuzzy networked control systems with uncertain parameters and external disturbance,such as event-triggered controller/filter design and fault diagnosis.A novel event-triggered fuzzy controller/filter is designed by combining of interval type-2 fuzzy system modeling method,time-delay system analysis method and slack matrix technology.Parts of the proposed results of this dissertation are applied to the mass-spring-damper system and tunnel diode circuit system.The simulation examples verify the effectiveness of proposed methods,The main contents are given as follows:Chapters 1-2 systematically introduce and summarize the background and development of networked control systems,event-triggered scheme and interval type-2 fuzzy control method,and gives some preliminary knowledge related to this dissertation.Chapter 3 investigates the problem of fuzzy controller design with system output information and event-triggered transmission strategy for networked interval type-2 fuzzy systems.The uncertainties of physical systems can be effectively solved by utilizing the membership functions with upper and lower bounds.In order to reduce the amount of data transmission in the network,an event-triggered communication mechanism is adopted.Considering the event-triggered transmission strategy and transmission delay,a novel dynamic output feedback controller is proposed.The proposed controller and the fuzzy model use different forms of membership functions.Consequently,the closed-loop system is with mismatched membership functions,which hampers the stability analysis and controller design.In order to promote stability analysis and achieve better control performance,this chapter uses the information of membership functions and relaxation matrix method to obtain the main results.Finally,the proposed method is applied to the mass-spring-damper system to verify the effectiveness of the proposed mechanism.Chapter 4 investigates the problem of filter design utilizing system output information and event-triggered transmission strategy for networked interval type-2 fuzzy systems.A novel design method of fuzzy filter is proposed for guaranteeing asymptotic stability and H? performance of filtering error system,where the premise variables are different from those of the fuzzy model.This chapter focuses on the filter design with uncertain parameters of the considered system,data quantization,communication delay and eventtriggered transmission strategy.The proposed event-triggered filter design communication mechanism with switching threshold has the advantage of saving network resources and provides flexibility in balancing the tracking error and the amount of data transmission in the network.Finally,the proposed method is applied to the tunnel diode circuit model to verify the effectiveness of the proposed scheme.Chapter 5 investigates the problem of output tracking control based on eventtriggered transmission strategy and network-induced delays for networked nonlinear control systems approximated by a class of interval type-2 fuzzy systems.The mechanism of upper and lower bound membership functions is used to deal with the modeling uncertainty in physical systems effectively.A fuzzy output tracking controller for controlling physical systems and tracking reference signals is proposed,where the premise variables and membership functions are asynchronous and different from those of the fuzzy systems,The results show that the proposed event-triggered transmission strategy with adaptive threshold is effective to reduce the frequency of data transmission.Finally,the proposed method is applied to the mass-spring-damper model to verify the effectiveness of the proposed mechanism.Chapter 6 investigates the fault diagnosis of networked nonlinear control systems based on event-triggered strategy under the framework of interval-2 fuzzy systems.In the system model,membership functions with the upper and lower bounds can effectively deal with the parameter uncertainty.In order to reduce the amount of data transmission in the network,an event-triggered communication strategy is adopted.In this chapter,a fault diagnosis filter by considering event-triggered communication mechanism,data quantization and communication delay is designed to generate a residual signal and detect system faults,where the premise variables are different from those of the system model.Consequently,the augmented fault detection system is with imperfectly matched membership functions,which hampers the stability analysis and fault detection.To relax the stability analysis and achieve better fault detection performance,the information of physical systems and slack matrices are utilized in the stability analysis.Finally,the proposed method is applied to the tunnel diode circuit model to verify the effectiveness of the proposed mechanism.Chapter 7 deals with the event-driven fault diagnosis problem for networked discretetime fuzzy control systems with nonlinear perturbations.In order to reduce the burden of communication bandwidth in the network,an event-triggered transmission strategy is used.A fault diagnosis fuzzy filter based on system output information is constructed to design fault diagnosis threshold and diagnose actuator fault by considering the eventdriven strategy,nonlinear perturbations,communication delay,and mismatched membership functions.The results show that the proposed event-driven fault detection technique can effectively save network resources compared with the time-triggered strategy.Finally,the proposed method is applied to the tunnel diode circuit model to verify the effectiveness of the proposed mechanism.Chapter 8 summarizes the results of the dissertation and points out the future research topics.