Robust Internal Model Control for Motor Systems Based on Sliding Mode Technique and Extended State Observer
Ping Li, Kaiqi Guo, Chenyang Sun, Mingming Zhang
Abstract
Electric motors have been widely used as the actuators of robot and automation systems. This paper aims at achieving the high-precision position control of motor drive systems. For this purpose, a robust control scheme is presented by combining the internal model principle, the sliding mode technique and the extended state observer (ESO). The PID-type controller is firstly designed by using the internal model control (IMC) rules. Since the analysis of the IMC system is performed via a sliding surface, a robust sliding mode control (SMC) law is then synthesized to enhance the control ability of the system to uncertainties. However, this robust solution should make a trade-off between the chattering attenuation and the control accuracy. To handle this drawback, a linear ESO is employed to compensate the modeling errors for a higher control accuracy. The stability analysis is provided via a Lyapunov-based method, and the superiority of the proposed approach was validated by comparative experiments on a motor drive platform.
BibTeX
@inproceedings{iros2020_robustinternalmo,
title = {Robust Internal Model Control for Motor Systems Based on Sliding Mode Technique and Extended State Observer},
author = {Ping Li and Kaiqi Guo and Chenyang Sun and Mingming Zhang},
booktitle = {IROS 2020},
year = {2020}
}