A Fast Adaptive Disturbance Rejection Control for Motor Servo Systems

doi:10.7652/xjtuxb202106006

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A Fast Adaptive Disturbance Rejection Control for Motor Servo Systems

更新时间：2025-07-09

- A Fast Adaptive Disturbance Rejection Control for Motor Servo Systems
- Vol. 55, Issue 6, Pages: 44-52(2021)
- 作者机构：
  
  南京理工大学机械工程学院,南京,210094
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb202106006
  CLC： TH113
- Online First：10 June 2021，
  
  Published：2021
- 稿件说明：
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A Fast Adaptive Disturbance Rejection Control for Motor Servo Systems[J]. 2021, 55(6): 44-52.
DOI：

A Fast Adaptive Disturbance Rejection Control for Motor Servo Systems[J]. 2021, 55(6): 44-52. DOI： 10.7652/xjtuxb202106006.

摘要

为实现电机伺服系统在参数不确定性和未建模干扰共同作用下的高精度运动控制

提出一种基于有限时间参数估计的快速自适应抗扰控制(FADRC)方法。针对参数不确定性

通过引入一阶低通滤波运算和辅助中间变量

构造一种由跟踪误差、参数估计误差和系统状态估计误差复合驱动的新型参数自适应律

实现未知参数的在线快速更新; 针对未建模干扰

设计扩张状态观测器(ESO)进行估计并由前馈项补偿; 此外

借助反馈鲁棒项保证系统整体鲁棒性。基于Lyapunov稳定性理论的分析表明

所提出的控制方法可保证快速的参数估计性能和优异的跟踪控制效果。搭建了电动伺服实验平台进行测试

测试结果表明:相比基于传统自适应律的控制方法

所提出的新型控制方法的参数估计收敛速度提高约80%

跟踪误差最大值减小约13.8%。该方法可为实际机电系统的高精度伺服控制和快速参数辨识提供参考。

Abstract

A fast adaptive disturbance rejection control method(FADRC)based on finite-time parameter estimation is proposed to realize high precision motion control of motor servo systems under the combined effect of parameter uncertainties and unmodeled disturbances. For parameter uncertainties

a novel parameter adaptation law driven by a combination of tracking error

parameter estimation error and system state estimation error is constructed by introducing first-order low-pass filtering operations and auxiliary intermediate variables to realize the fast online updating of unknown parameters. For unmodeled disturbances

an extended state observer(ESO)is designed to estimate them and compensate them with a feedforward term. In addition

the overall robustness of the system is ensured by the feedback robust term. Analysis based on Lyapunov stability theory shows that the proposed control method can guarantee fast parameter estimation performance and excellent tracking control effect. An electric servo experimental platform is built to test its effectiveness and superiority. Test results and a comparison with the traditional adaptation law-based control method show that the proposed novel control method improves the convergence speed of parameter estimation by about 80% and reduces the maximum tracking error by about 13.8%. This method can provide reference for high precision servo control and fast parameter identification of practical electromechanical systems.

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