A Variable Parameter Method Based on Linear Extended State Observer for Position Tracking

Ying Zheng,Wei Jiang,Xinguo Qiu

doi:10.3390/act11020041

Abstract

This paper presents a control strategy with a linear extended state observer (LESO) and Kalman filter to achieve a high performance of the motion control system. The moment of inertia of the system, which is variable with the robotic joint motion, is estimated in the established model. A LESO with variable gain is designed, which could estimate the states and the total disturbance of the plant without a precision mathematical model. The disturbance caused by variable load and unknown dynamics can be compensated based on the LESO, while the moment of inertia is variable. In order to restrain the process noise and measure the noise of the system, the Kalman filter was applied. Tracking differentiator was utilized to avoid the overshoot of the system for the step signal. The designed control strategy with the LESO and the Kalman filter could improve the tracking performance for the servo system with parametric uncertainties, unknown dynamics, and disturbances. The effectiveness of the proposed method is implemented and validated in the experiment of the robotic joint, for which desired servo tracking performance is achieved with the conditions of load variation and sudden disturbance.

Highlights

With the increasing demands for the high performance of motion control systems, advanced control strategies have been applied to the motor drives
Among the previously listed approaches, extended state observer (ESO) does not require precise information of the plant; the internal dynamics and external disturbance are treated as total disturbance which could be estimated by ESO and compensated for the plant in real time by an active disturbance rejection controller (ADRC) [11]
A practical controller based on the linear extended state observer (LESO) and the Kalman filter (KF) was proposed for the position tracking of the robotic joint motion with variable inertia and unknown dynamics

Summary

Introduction

With the increasing demands for the high performance of motion control systems, advanced control strategies have been applied to the motor drives. The moment of inertia and load torque are variable in the model to approach the practical plant in which the total disturbance is estimated and rejected by ADRC to improve system performance. The objective of this paper was to design a controller based on ADRC and the Kalman filter to improve performance of a servo system of which the moment of inertia is variable. The LESO is the designed observer, KF is the designed Kalman filter used to reduce measurement noise, x1d is the reference signal, u0 is the control law without disturbance compensation, u is the control strategy, z3 is the estimation of the extended state variable obtained by the LESO, representing the effect of the total disturbance, and x1 is the angular position with noise suppression by KF.

LESO Design

Controller Design

Experiment Verification

Conclusions