Adaptive Fuzzy Control Design For Stochastic Nonstrict-feedback Nonlinear Systems

With the rapid development of modern science and technology,industrial control system as the theoretical basis of many industries is moving in the direction of complexity and scale,so the nonlinearity of control system becomes more and more obvious.On the one hand,non-smooth nonlinear function inputs such as quantization and backlash often exist in many practical engineering applications,which have a great impact on system performance.Therefore,for practical engineering systems,it is of great practical significance to study the stability analysis and controller design for a class of nonlinear systems with nonsmooth non-linear inputs.On the other hand,many control systems are subject to constraints to achieve the specified performance,with output limited and status limited.Therefore,under the condition of constraints,studying the stability of nonlinear systems is of great significance to the future development of control theory and the practical application of engineering systems.Although many researches on adaptive control of nonlinear systems already existed,many problems still need to be solved.Based on this,this dissertation will study a class of uncertain stochastic nonlinear systems by adaptive fuzzy control method as follows:In Chapter 2,we study a class of adaptive fuzzy control problems for a class of stochastic nonlinear systems in nonstrict-feedback form appearing dead-zone and full-state constrained.To improve the system performance,the barrier Lyapunov function is introduced to solve the problem of state limitation.The fuzzy logic system is used to approximate the unknown nonlinear function.In addition,a new adaptive fuzzy controller is designed based on the backstepping control design method,which is used to ensure that the mean square of all signals in the closed-loop system is finally uniformly bounded.Finally,a simulation example is given to verify the effectiveness of the proposed method.In chapter 3,we study a class of adaptive fuzzy control problems for stochastic nonstrict-feedback nonlinear systems which state is not measurable,taking into account the existence of unknown hysteresis.In the process of controller design,fuzzy logic system is used to directly estimate unknown nonlinear function,and fuzzy observer is used to observe state variables.By combining backstepping with dynamic surface technology,a new adaptive fuzzy control method is proposed.The controller designed in this paper can guarantee that all the signals are uniformly bounded in the mean square of the closed-loop system.And through the online adjustment of multiple design parameters,the system output converges to a small neighborhood of the origin.