Fuzzy-model-based fault-tolerant design for nonlinear stochastic systems against simultaneous sensor and actuator faults

This paper addresses the problem of fault estimation and fault-tolerant control for a class of Takagi-Sugeno (T-S) fuzzy Itô stochastic systems subject to simultaneously sensor and actuator faults. The main difficulty in this study is that sensor faults, actuator faults, and stochastic noise that are governed by Brownian motion are taken into simultaneous consideration in a unified framework, and traditional fault-tolerant approaches are not effective to solve this research issue. A new descriptor fuzzy sliding-mode observer approach is presented in this paper to obtain the simultaneous estimates of system state, sensor fault, and actuator fault vectors. Based on the state estimates, an observer-based fault-tolerant control (FTC) scheme is developed to stabilize the resulting closed-loop system. Finally, a simulation example is provided to show the effectiveness of the proposed fault-tolerant approach.