Adaptive Prescribed Performance Fault Estimation and Accommodation for a Class of Stochastic Nonlinear Systems

This paper studies the problem of adaptive fault estimation and accommodation for a class of stochastic nonlinear systems with unknown time-varying faults. Different from existing fault estimation methods, a novel adaptive prescribed performance fault estimator is designed, which guarantees that the fault estimation error is confined within a pre-set region, and a better estimation accuracy is obtained. The designed fault-tolerant tracking controller is capable of attenuating the effect of faults through using back-stepping techniques. Furthermore, the proposed method guarantees that all the error signals of the closed-loop system be bounded in probability, the fault estimation error and output tracking error both converge to desired neighborhoods of origin in the sense of quadratic mean value. Finally, the simulation results are provided to verify the method proposed in this paper.