Adaptive Fuzzy Prescribed Performance Control For Stochastic Nonlinear Systems

In this thesis,under the framework of adaptive fuzzy control and prescribed performance control theory,the adaptive fuzzy prescribed performance control(PPC)designs and stability analysis problems are studied for several classes of uncertain stochastic nonlinear systems.The main works as follows:(1)For a class of uncertain stochastic nonlinear systems with a non-triangular structure,the problem of the prescribed performance fuzzy adaptive state feedback control design is considered.In the control design,the fuzzy logic system is used to model the controlled systems.By combining the prescribed performance theory with the fuzzy adaptive backstepping design framework,an adaptive fuzzy state feedback controller is developed.It is proved that the proposed control approach can guarantee the stability in probability of the closed-loop system and the tracking errors remain a small neighborhood of the origin within prescribed performance boundedness(PPB).A numerical simulation example is provided to illustrate the effectiveness of the proposed approach.(2)For a class of multi-input and multi-output(MIMO)stochastic nonlinear systems with unknown dead zones and unknown control directions,the problem of the prescribed performance fuzzy adaptive output feedback control design is considered.In the control design,the fuzzy logic systems are utilized to approximate the unknown nonlinear functions,based on the adaptive fuzzy backstepping design method and the prescribed performance control theory,an adaptive output feedback prescribed performance control approach is developed.It is proved that the proposed control approach can guarantee the stability of the closed-loop system in probability.The effectiveness of the proposed approach is illustrated by a simulation example.(3)For a class of stochastic nonlinear interconnected systems,the problem of the prescribed performance fuzzy adaptive decentralized control design is considered.In the control design,the fuzzy logic system is used to model the controlled systems,based on the theory of prescribed performance control and the fuzzy adaptive backstepping design method,a fuzzy adaptive prescribed performance decentralized controller design scheme is proposed.The stability in probability of the closed-loop system is proved by stochastic Lyapunov stability theory.The effectiveness of the proposed control method is further verified by numerical simulation.(4)For a class of stochastic interconnected uncertain nonlinear systems with input time delay,the problem of the prescribed performance fuzzy adaptive decentralized control design is considered.In the control design,the pade approximation method is introduced to solve the input time delay problem and the fuzzy logic system is used to identify the unknown nonlinear functions in the system.By combining the adaptive backstepping design method with stochastic Lyapunov stability theory,an adaptive fuzzy output tracking prescribed performance decentralized control scheme is given.The stability of the closed-loop system in probability is proved via stochastic Lyapunov function method.The effectiveness of the proposed approach is illustrated by a simulation example.