Robust Control For Two Classes Of Nonlinear Stochastic Systems With Time-delays Based On Dissipative Analysis

In engineering practice,many practical control system phenomenon can not avoid time delay,and the time delay is considered in engineering,mechanics,control theory,it is the main reason to produce shock and instability,however,the influence of delay is not just on the system,and it is the objective existence.The loss cased by the random error is immeasurable,so it is particularly important to study of stochastic time-delay systems.In this paper,it is discussed about the nonlinear time-varying delay system of dissipative analysis and nonlinear stochastic neutral system of passivity analysis,Lypaunov functions are different for different nonlinear systems.This paper is divided into four chapters to explain:In the first part,the main contents are described in general,and the necessity of the study is pointed out.The second part,it is discussed about the dissipative analysis for a class of nonlinear time-varying delay systems,it is divided into delay-independent dissipative analysis and delay-dependent delay dissipative analysis,according to the structure of the system and the knowledge of LMI and the definition of dissipativity,sufficient condition of the controller is given as nonlinear matrix inequality,and then through the equivalent transform,it is given as the linear matrix inequality,also it gives the method to design the feedback controller,the conclusions are proofed by numerical examples.In the third part,it is considered about the finite-time passification for nonlinear neutral stochastic systems with uncertainties and time-varying delay,it is divided into delayindependent dissipative analysis and delay-dependent delay dissipative analysis and then design controllers about memory controller and memoryless controller,combining the Lyapunov-Krasovskii function with inequality scaling and the definition of finite time,sufficient conditions are shown for the system,the conclusions are proofed by numerical examples.Finally,it focus on summarizing this paper and points out the next research direction,our research not only enrich the control theory of nonlinear systems,but also expand the research methods of stochastic systems.Numerical simulation examples also illustrate the correctness of the conclusions.