Abstract:

A model-free control method is proposed for trajectory tracking of multi-degree of freedom robotic manipulator to deal with the problems of relying too much on the precise mathematical model and low tracking accuracy. This method combines the adaptive neural network, the ultra-local model and the integral terminal sliding mode. First, an ultra-local model based on delay estimation is used to approximate the dynamic model of the manipulator. Then, a neural network is used to compensate the errors of delay estimation because of its nonlinear approximation capability. Finally, an integral sliding mode controller is designed for the ultra-local model to improve the convergence speed and control accuracy of the system and realize the high-precision trajectory tracking of the manipulator without relying on the dynamic model. The stability and finite time convergence of closed loop system are proved by Lyapunov theory. Experimental results show that the proposed control method can realize the high precision tracking control of the manipulator without depending on the model information completely.

Key words: automatic control technology, robotic manipulator, ultra-local mode, sliding mode control, neural network, trajectory tracking, finite time convergence