Adaptive finite-time fault-tolerant control for Robot trajectory tracking systems under a novel smooth event-triggered mechanism

Abstract

The problem of adaptive finite-time fault-tolerant control with smooth event-triggered mechanism is addressed for quadrotor trajectory tracking systems. In light of recent studies on fault-tolerant control in the field of nonlinear systems, this article focuses on quadrotor trajectory tracking systems with actuator faults and disturbances. Different from the previous works, an ingenious smooth event-triggered mechanism is proposed to circumvent the discontinuous triggered signal and alleviate the communication burden simultaneously, which is of great significance to increase the operation life of the quadrotor. Subsequently, the finite-time performance function is designed to guarantee the prescribed tracking performance. Furthermore, a novel finite-time convergent adaptive fault-tolerant controller is proposed via the time-varying barrier Lyapunov function technique. The radial basis function neural networks are utilized to deal with the nonlinear approximation, and the adaptive laws are developed to accurately estimate the unknown model uncertainty, thus effectively handling the challenge of the controller design caused by the actuator faults and disturbances. Under the developed adaptive fault-tolerant controller, all the closed-loop system signals are bounded and the tracking errors are convergent within finite time. Meanwhile, the Zone behavior can be excluded by the positive sampling intervals. Finally, two examples are employed to verify the effectiveness and advantages of the suggested control scheme.