Networked Control For T-S Fuzzy Systems Under Two Kinds Of Sampling Schemes

The networked control problem for T-S fuzzy systems under two kinds of sampling schemes is studied in this thesis.In practical industrial applications,the controlled plant is sam-pled by sensors with different sampling periods in order to improve the system perfor-mances.Since the insertion of the communication network in control systems can result in network-induced delays and packet losses inevitably,how to fully utilize the characteristics of network-induced delays and packet losses in modeling,analysis and design of networked control systems is a crucial issue to be concerned with.The main research contents of this thesis include two parts.The first part studies the event-triggered based networked control problem of a T-S fuzzy system by using a markov chain to describe the delay interval in such a system,where the sampling scheme is single rate.The second part concerns the networked control problem for a T-S fuzzy system,where the sampling scheme is dual-rate.The research work of this thesis is organized as follows:(1)The first chapter introduces the networked control systems,T-S fuzzy systems,multi-rate sampling systems and their research status at home and abroad,and then presents the main research contents of this thesis.(2)The second chapter considers the networked L2-gain control problem for a T-S fuzzy system under an event-triggered communication scheme.Taking an event-triggered communication scheme and network-induced delays into consideration,the networked control system is described by an asynchronous T-S fuzzy system with an interval time-varying delay.Due to the varying characteristic of network-induced delays,the interval is decomposed into N subintervals and the jumping behavior among these subintervals is governed by a markov chain.Moreover,a new relaxation method,which fully utilizes the convexity of normalized membership functions and the deviation bounds of asyn-chronous normalized membership functions,is proposed and a stochastic Lyapunov-Krasovskii functional is constructed to derive some results of the stochastic stability criterion and fuzzy controller design for the asynchronous T-S fuzzy system.A nu-merical example is provided to illustrate the effectiveness of the proposed method,and shows that the proposed results are of less conservatism and less computational com-plexity than some existing results.(3)In the third chapter,the networked H? control problem for a dual-rate sampling T-S fuzzy system is investigated by considering network-induced delays and packet losses in a network environment.The measured output variables of the controlled plant are sampled by two kinds of sensors with different sampling rates.Taking the influence of the dual-rate sampling,network-induced delays and packet losses into account,the networked control system with dual-rate sampling is modeled as a T-S fuzzy system with two interval time-varying delays.Applying the Lyapunov-Krasovskii functional method,some results of stability criterion and dynamic output feedback controller de-sign for the T-S fuzzy system are presented in terms of linear matrix inequalities.A simulation example is given to demonstrate the validity of the proposed method,and verifies that the obtained criteria for a dual-rate sampling system are of less conser-vatism than the results of the corresponding single-rate sampling system.(4)The fourth chapter summarizes the main research work of this thesis,and points out the future work.