Sampled-data Control Of T-S Fuzzy Time-delay System

T-S fuzzy control can combine strict mathematical theory with the applicability of linear system,so it can effectively solve the problems of non-linearity,time delay and uncertainty disturbance of the controlled object in the actual engineering system.In addition,since the sampled-data control only receives the sampled pattern and uses discrete-time signals,this will greatly reduce the implementation cost and time,so the sampled-data control has the characteristics of high efficiency and practicality.Therefore,this paper mainly discusses the stability analysis and application of T-S fuzzy time-varying delay system based on sampleddata control,as well as the research of performance indicators.At the same time,this paper combines the effects of uncertain terms,actuator saturation,and state quantification on the system,constructs the Lyapunov-Krasovskii function,introduces a new integral inequality lemma,solves LMI and other methods,analyzes the dissipative performance of the system,and designs ideal non-linear Fragile sampling fuzzy controller.The main contents of this paper are:Firstly,for an uncertain T-S fuzzy time-varying delay system,the exponential stability and H∞ performance index are analyzed,and an effective fuzzy sampled-data controller is designed.Using the Matlab toolbox to solve the linear matrix inequality(LMI),the controller gain is obtained.Prove the practicability of the method by simulating practical examples.Secondly,by constructing the augmented Lyapunov-Krasovskii function,the dissipative stability of uncertain T-S fuzzy time-delay systems is studied,and the design method of non-fragile sampled-data fuzzy controller is given.At the same time,adding the limitation of actuator saturation makes the required non-fragile sampled-data fuzzy controller more flexible in order to improve the performance of the system.Finally,the problem of exponentially stable dissipation of uncertain time-varying delay T-S fuzzy system with state quantization is studied,and a non-fragile sampled-data quantitative fuzzy controller is designed.By using integral inequality and Newton-Leibnitz formula,sufficient conditions are obtained for the system to satisfy both exponential stability and strict dissipation.Finally,an example is given to prove the feasibility and effectiveness of the design method.