Sliding Mode Control For Stochastic System Against Actuator Faults

In recent years,with the development in technology,the demand for the accuracy of control systems in practical applications is more rigorous,however the traditional deterministic system model cannot meet the demand high of high precision.In addition,stochastic factors and actuator faults are often the source of performance degradation and instability.And the information of actuator faults and stochastic factors are sometimes unknown.Therefore,the study of stability and controller design for stochastic system with actuator faults has become an attractive problem.Although the sliding mode control has good ability to completely compensate for external disturbance and model uncertainties satisfying the matching condition,when the state of the system is unknown,this method is infeasible.To overcome this difficulty,adaptive control method which is a good measure to control the systems with unknown parameter can be taken this account.This thesis combines the sliding mode control with adaptive control method to design controller for linear system and stochastic system with unknown parameter.The main contributions are summarized in the following several respects:Firstly,this thesis investigates the problem eliminate of fault estimation and adaptive integral sliding mode tolerant control against time-varying actuator fault and full-state unknown for a class of linear systems.By using adaptive integral sliding mode observer mechanism and an auxiliary system which is designed to the estimation error,an estimation of the system states and fault vector are estimated,simultaneously.Based on the estimated states and fault vector,an adaptive integral sliding mode fault tolerant control scheme is proposed to stabilize the fault system and restrain disturbance.It is shown that the designed controller can ensure the resulting closed-loop system is asymptotically stable and the estimation error converges to zero.Secondly,for the Markov jump system(MJS)with unknown parameter,a sliding mode estimation mechanism is designed to estimate unknown parameter and actuator faults to guarantee the stability.Furthermore,in order to avoid the influence caused by transition probability in LMI,two different Lyapunov functions are employed with respect to the error system and observer system.Finally,the effectiveness of the presented scheme is elaborated by an example.Thirdly,in order to expand the scope of application,the Ito stochastic system is considered.The state and actuator estimation and feedback stabilization problems are studied.New method is proposed to construct the adaptive controllers.A sliding intermediate estimator is designed by using stochastic Lyapunov method.And the sliding adaptive controller is designed to guarantee that the closed-loop system is stochastic stable.Then,sufficient conditions for the existence of parameters and actuator estimation are obtained.Finally the summary of this dissertation and prospect of the research development are given.The main contributions of this dissertation are summarized and some open problems are also pointed out which deserve further study.