Adaptive Fuzzy Finite-time Tracking Control for A Class of DC Motor with State Constraints

This paper presents an adaptive fuzzy finite-time control scheme for a class of direct-current (DC) motor with state constraints. Firstly, the barrier Lyapunov function is used to constrain the state variables of the DC motor to ensure that the angular position and angular velocity of the DC motor are limited within the given constraint range. Secondly, the fuzzy logic system is introduced to approximate the unknown nonlinear function, and the finite-time control technology is utilized to improve the convergence speed and control accuracy of the system. Finally, the simulation results show that the proposed method can achieve fast and effective position tracking control for DC motor.