Adaptive fuzzy finite-time control of stochastic nonlinear systems with actuator faults

This paper considers the finite-time control problem for a class of nonlinear stochastic systems with actuator faults/failure. A fast convergence feedback control algorithm based on backstepping finite-time command filtering is proposed. Under the framework of adaptive feedback, the fuzzy logic system is used to deal with the uncertainties of the system. Taking into account the actuator faults of both loss of effectiveness and lock-in-place, an adaptive fuzzy controller is developed. Since there is no need to calculate the derivative of the virtual control signal, the presented scheme overcomes the “explosion of complexity” problem inherent in conventional methods. A compensation mechanism is also introduced to compensate for errors caused by the filter. The proposed method ensures not only that all signals of the closed-loop system are finite-time bounded, but also that the tracking error converges to a small neighborhood around the origin. The effectiveness of the proposed method is demonstrated in the simulation results.

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