H_? Control For Stochastic Nonlinear System Based-on Backstepping Technique

Because stochastic factors extensively exist in many practical systems,so the stochastic systems control problem received the attention of many scholars.Considering stochastic systems will suffer from external disturbances which will affect the stability and control accuracy of stochastic systems,the five relevant problems about H_?control of stochastic nonlinear systems are studied based on backstpping technique in this paper.The main innovation points are as follows:1.The bounded-H_?tracking control problem is studied for a class of stochastic systems with known nonlinear functions.The concept about bounded-H_?is proposed for the first time.Based on the concept,a new way to design H_?controller of stochastic nonlinear systems is proposed by combining backstepping technique,Lyapunov stability theory with H_?theory.The designed controller guarantees that all the signals in the controlled system are bounded in probability,and the tracking control performance is achieved.At the same time,and the controlled system has a given H_?performance for external disturbances.The simulation results are presented to verify the effectiveness of the proposed control strategy.2.The bounded-H_?adaptive tracking control problem is studied for a class of stochastic systems with completely unknown nonlinear functions.In the control design,RBF neural networks are used to deal with the packaged unknown nonlinear functions,and a bounded-H_?adaptive tracking control method is proposed.The method can guarantee that all the signals in the controlled system are bounded in probability,and the tracking performance of the system is achieved,and the system satisfies a given H_?performance index for external disturbances.At the same time,only two adaptive estimation parameters are needed for n-order stochastic nonlinear systems,so it is convenient that the proposed control scheme is applied to actical devices.The simulation results are given to verify the effectiveness of the proposed control scheme.3.The prescribed performance bounded-H_?adaptive tracking control problem is studied for a class of stochastic systems with completely unknown nonlinear functions,in which both drift fields and diffusion terms are influenced by external disturbances.In the control design,the prescribed performance function is applied to restrict the tracking error of the system,and a bounded-H_?adaptive tracking method is proposed.The designed controller guarantees that the system has a good tracking performance,and all the signals in the closed-loop system are bounded in probability,meanwhile,and the system has an H_?performance for external disturbances.The simulation results are presented to verify the effectiveness of the control scheme.4.The H_?stabilization problem is studied for a class of stochastic interconnected large-scale systems with completely unknown nonlinear functions,and a design scheme for decentralized adaptive bounded-H_?controller is proposed.The designed decentralized controllers guarantee that all the signals in the closed-loop large-scale system are bounded in probability,and the every subsystem has an H_?disturbance attenuation performance for external disturbances.The effectiveness and feasibility of the proposed scheme are verified by the simulation results.5.The H_?tracking control problem is studied for a class of stochastic time-delay systems with completely unknown nonlinear functions.In the control design,Lyapunov-Krasovskii functionals are constructed to compensate the time-delay terms,and an adaptive bounded-H_?tracking control scheme is proposed.The controller is designed according to the proposed scheme,which guarantees tracking performance,H_?performance of the controlled system,and boundness in probability of all the signals in the system.A simulation example is given to demonstrate the reasonability and efficiency of the proposed method.