A Novel Practical Robust Control Inheriting PID for SCARA Robot
Shengchao Zhen, Ziyi Zhao, Xiaoli Liu, Chen Feng, Han Zhao, Ye‐Hwa Chen
Abstract
In this paper, we propose a novel practical robust control algorithm for the Selective Compliance Articulated Robot Arm (SCARA) robot and verify the effectiveness through experiments. The dynamic model of the SCARA robot is established considering uncertainties, which include the nonlinear friction, parameter uncertainty, and external disturbance. To restrain the reversal chattering, we apply a modified Stribeck friction model with Gaussian compensation term as the friction description. The algorithm is composed of a proportional-derivative (PD) feedback term based on the model and a robust term. The formation of the robust part comprises the upper bound of the uncertainty. The Lyapunov minimax method is adopted to prove that the system is uniformly bounded and uniformly ultimately bounded, thus guaranteeing the practical stability of the system. Moreover, rapid controller prototyping cSPACE, as the experimental platform, can eliminate the tedious programming work and provide a great convenience for the experiments. The experimental results indicate that the robust control algorithm has good performance, which provides accurate trajectory tracking under the influence of uncertainties.