Adaptive Faster Fixed-Time Nonsingular Terminal Sliding Mode Control for Manipulator Systems

In this paper, a controller which can achieve fixed-time convergence is studied for manipulator systems. Firstly, an adaptive neural network (ANN) is used to estimate the unknown parts and external disturbances of the system. Secondly, a piecewise sliding mode variable is used to realize the nonsingular control of the terminal sliding mode. Then, in order to improve the tracking speed of the manipulator system, a faster fixed-time control algorithm is designed, and the tracking error can converge within a faster fixed-time. Finally, the practicability of the proposed algorithm is verified by simulation.