Fault-Tolerant Control of Stochastic Strict-Feedback Nonlinear Systems With Multiple Faults

In this article, we study the fault-tolerant control (FTC) issue of stochastic nonlinear controlled plants. The considered plant is of strict-feedback form, which subjects to multiple faults, i.e., sensor and actuator faults. For the purpose of estimating the unmeasured system state vectors, a neural-network-based observer is presented. With the help of a combined quadratic, cubic, and quartic Lyapunov functional candidate, a new type of adaptive FTC strategy is formulated to ensure the overall tracking performance with multiple faults. Besides, the corresponding stability analysis is carried out as well. Comparing with the simulation results without fault compensation strategy, the validity of the designed FTC mechanism is verified.