Adaptive block compensation trajectory tracking control based on LuGre friction model

Abstract

Aiming at the problems of modeling error and uncertain external disturbance in the multi-joint robot control model, an adaptive block compensation trajectory tracking controller based on LuGre friction model is proposed. Firstly, the algorithm divides the interference term of LuGre friction model into three parts with different physical quantities. Secondly, an adaptive neural network compensator is designed to assess the three parts of the LuGre friction model. Thirdly, a robust sliding mode controller is developed to reduce the influence of these estimation errors of neural network compensator and other uncertain disturbances and ensure that the system converges in a finite time at the same time. Finally, numerical simulations under different input and disturbance signals for the planar multi-joint robot and the inverted pendulum are conducted to validate the effectiveness of the proposed controller, and the performance of the proposed controller is compared with conventional sliding mode controller to illustrate the usefulness and efficiency of the proposed controller.