Extended state observer–based sliding mode learning control for mechanical system

Bing He,Gang Liu,Xiaoxiang Hu,Hailong Chen

doi:10.1177/0020294020927424

Abstract

A novel sliding mode learning controller is proposed for uncertain mechanical system in this paper. The model of uncertain mechanical system is listed first, and then extended state observer is designed for the estimation of the uncertainty. Then, an extended state observer–based sliding surface is constructed. The sliding surface parameters are solved by Lyapunov function approach. Then, a sliding mode learning controller is proposed for uncertain mechanical system to overcome the inherent chattering. Finally, a numerical simulation is given to show the effectiveness of the proposed sliding mode learning controller.

Highlights

Uncertainty is inevitable in actual production process and will certainly bring bad influence to the control performance of a real system
If the uncertainty can be estimated online, and a robust controller can compensate it in real time, the control performance will be much better and the amount of computation will greatly reduce
An Extended state observer (ESO) is constructed to estimate the unknown parameter uncertainty and disturbance, and an ESO-based sliding surface is proposed for uncertain mechanical system; 3

Summary

Introduction

Uncertainty is inevitable in actual production process and will certainly bring bad influence to the control performance of a real system. ESO is utilized here to estimate the uncertainty and disturbance, and an ESO-based sliding surface is constructed and its stability is guaranteed by selecting parameters appropriately. After getting the sliding surface, a learning controller is proposed for the uncertain mechanical system model.

Results

Conclusion