Research On Adaptive Tracking Control For Stochastic Nonlinear Systems Based On Event Triggering Strategy

In practical engineering,the controlled objects are generally nonlinear,and are often disturbed by random disturbances.Therefore,the research on uncertain stochastic nonlinear systems has both theoretical significance and practical application value.In addition,more and more systems use communication networks to transmit data.However,the bandwidth of the transmission channel is limited.The waste of communication resources is caused by the traditional periodic sampling mode.In recent years,event-trigger control has been paid attention to by scholars.How to design a safe and reasonable controller to make the system run normally and stably,and to make it achieve the purpose of improving its resource utilization is the focus of the current control field.In this paper,the problem of adaptive event triggered fuzzy tracking control for stochastic nonlinear systems is discussed under the condition of actuator saturation and state unmeasurable.The main research contents of this paper are shown as follows:Chapter 1 introduces the research background of the related contents,the research status of stochastic nonlinear systems,the principle and development of event triggering,and expounds the research significance and value of adaptive event triggered fuzzy tracking control for stochastic nonlinear systems.Chapter 2 gives some basic knowledge related to this paper.In chapter 3,an adaptive event-triggered control method based on fuzzy approximation is proposed for pure feedback stochastic nonlinear systems with input saturation.In order to solve the problem of saturation nonlinearity in nondifferentiable state,a smooth nonlinear function is introduced to approximate the saturation function.Secondly,an adaptive event triggered tracking controller based on mean value theorem is designed by using backstepping method.The proposed controller ensures that all the signals in the closed-loop systems are bounded in probability and the tracking error converges to a small neighborhood of the origin.Finally,the simulation results verify the effectiveness of the control scheme.In chapter 4,the adaptive event-trigger fuzzy tracking control for uncertain stochastic nonlinear systems with unknown state is discussed.Firstly,a robust fuzzy state observer is designed to estimate all unmeasurable states.Then using backstepping method,an adaptive output feedback controller which can adjust parameter update law online is designed.At the same time,an event triggering condition with tracking error decreasing function is introduced,which effectively reduces the computational load in the communication process.Finally,two simulation examples are given to verify the method in this chapter.The simulation results show that the tracking error can converge to the small neighborhood of the origin,and all signals in the closed-loop system are bounded in probability,which verifies the effectiveness of the proposed method.Chapter 5 summarizes the results of the dissertation and pointed out the future research.