Research On Robust Dissipative Tolerant Control For T-S Fuzzy Sampled-data System

Due to the long time and heavy load of modern industrial process systems,actuators or sensors are inevitably malfunctioning.Tolerant control is an effective method to solve the above problems.The smooth nonlinear sampled-data system can be approximated as a linear T-S fuzzy sampled-data system described by the IF-THEN fuzzy rules.The above T-S fuzzy model provides an effective solution to the analysis and synthesis of nonlinear control systems.On the other hand,dissipative theory has become an important tool for the analysis and design of nonlinear control systems.At the same time,dissipative control can unify control and passive control and provide a more flexible and less conservative method for nonlinearly controlled sampled-data systems.Therefore,it is of great theoretical value and practical significance to study the robust dissipative tolerant control problem of nonlinear T-S fuzzy sampled-data systems.In this paper,linear matrix inequalities(LMI)are used as the main mathematical tools to study the robust dissipative tolerant control problem for nonlinear T-S fuzzy sampled data systems with actuator failures and the nonlinear T-S fuzzy sampled data systems with state quantization.The new Lyapunov-Krasovskii Function(LKF)and the less conservative boundary processing method are selected.Using the input delay method,the stability criterion of the T-S fuzzy sampled-data system is given and the desired controller is designed.The main contents of the full text are summarized as follows:(1)For the nonlinear T-S fuzzy sampled-data system with actuator failure,the problem of robust dissipative tolerant control is studied.A new LKF and Bessel-Legendre integral inequality processing technique is selected to obtain a less conservative stability condition and a tolerant controller based on dissipative analysis is designed.In addition,given the absence of actuator failure and rigorous ? dissipative,a sufficient condition for the asymptotic stability of the T-S fuzzy sampled-data system is given.The results show that the new stability criterion provides a larger upper sampling-interval than other existing methods.(2)For the nonlinear T-S fuzzy sampled-data system with state quantization and actuator failure,the problem of robust dissipative tolerant control is studied.By choosing discontinuous LKF,applying the Free-Matrix-Based integral inequality boundary processing technique and dissipative control theory,a less conservative stability condition is obtained and a controller that guarantees system performance is designed.At the same time,the above theoretical results are applied to discuss the stability of the T-S fuzzy sampled-data system with state quantization and the T-S fuzzy sampled-data system based on the dissipative analysis,respectively.The required sampled-data controllers are designed.The results show that the application of the theoretical method in this chapter is superior to the existing literature results whether it is the maximum sampling interval based on state quantization or the optimal performance index based on dissipative analysis.In the end,the work done in this thesis is summarized,and some problems in the theoretical research of T-S fuzzy sampled-data control system are pointed out,and further development directions are pointed out.The future research work is prospected.