柔性关节机械臂的自适应命令滤波输出反馈控制

潘昌忠; 费湘尹; 周兰; 熊培银; 李智靖

doi:10.7652/xjtuxb202205020

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柔性关节机械臂的自适应命令滤波输出反馈控制

更新时间：2025-07-09

- 柔性关节机械臂的自适应命令滤波输出反馈控制
- Adaptive Command Filtered Output Feedback Control for Flexible Joint Manipulator
- 西安交通大学学报 2022年56卷第5期页码：199-208
- 作者机构：
  
  湖南科技大学信息与电气工程学院,湖南,湘潭,411100
- 作者简介：
  
  : 2021-12-13。作者简介: 潘昌忠(1984—),男,博士,副教授。基金项目: 国家自然科学基金资助项目(62173138)
- 基金信息：
  
  : 2021-12-13。作者简介: 潘昌忠(1984—),男,博士,副教授。基金项目: 国家自然科学基金资助项目(62173138);湖南省自然科学基金资助项目(2019JJ50157);湖南省教育厅科学研究重点资助项目(20A186)
- DOI：10.7652/xjtuxb202205020
  中图分类号： TP24
- 网络首发：2022-05-10，
  
  纸质出版：2022
- 稿件说明：
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潘昌忠, 费湘尹, 周兰, 等. 柔性关节机械臂的自适应命令滤波输出反馈控制[J]. 西安交通大学学报, 2022,56(5):199-208.

PAN Changzhong, FEI Xiangyin, ZHOU Lan, et al. Adaptive Command Filtered Output Feedback Control for Flexible Joint Manipulator[J]. 2022, 56(5): 199-208.
潘昌忠, 费湘尹, 周兰, 等. 柔性关节机械臂的自适应命令滤波输出反馈控制[J]. 西安交通大学学报, 2022,56(5):199-208. DOI： 10.7652/xjtuxb202205020.

PAN Changzhong, FEI Xiangyin, ZHOU Lan, et al. Adaptive Command Filtered Output Feedback Control for Flexible Joint Manipulator[J]. 2022, 56(5): 199-208. DOI： 10.7652/xjtuxb202205020.

摘要

针对柔性关节机械臂轨迹跟踪控制中存在模型摄动、外界干扰以及部分状态信息不可测等问题

提出一种基于自适应神经网络观测器的命令滤波输出反馈控制方法。首先

给出含不确定性的柔性关节机械臂动力学方程

并选用RBF神经网络设计自适应律

在线逼近由模型摄动及未知干扰带来的不确定性项; 然后

设计自适应神经观测器以对系统不可测状态进行实时估计

并将估计值用于反馈控制

解决部分状态信息不可测的问题; 最后

基于Lyapunov理论设计反步跟踪控制器

并引入二阶命令滤波器获得中间虚拟控制量的导数

避免反步递推过程中“计算爆炸”的问题。仿真结果表明

当系统存在模型摄动和外界干扰时

所提自适应命令滤波反步控制方法与传统反步控制方法和误差补偿命令滤波控制方法相比

无需连杆的角速度以及电机轴的转角和角速度等状态信息

且轨迹跟踪精度分别提升78%和35%。

Abstract

To address such problems as model perturbation

external disturbance and state undetectability in the trajectory tracking control of a flexible joint manipulator(FJM)

a command filtered output feedback control method based on adaptive neural network observer is proposed. Firstly

the dynamic equation of the FJM with uncertainties is given

and adaptive laws are designed by using RBF neural networks to approximate online the uncertainties caused by model perturbations and unknown disturbances. Then

an adaptive neural observer is designed to estimate undetectable states in a real time manner

and the estimated values are used for feedback control to solve the problem of undetectability. Finally

a backstepping tracking controller is designed based on Lyapunov theory

and second-order command filters are introduced to obtain the derivatives of the intermediate virtual control laws

where the problem of “calculation explosion” in the backstepping recursive process is avoided. Simulations are conducted for the FJM in the presences of model perturbations and external disturbances

and the results show that compared with the traditional backstepping control method and the command-filtered method with error compensation

the proposed method does not require some state information like the angular velocity of the link and the angle and the angular velocity of the motor shaft. Moreover

the trajectory tracking accuracy is improved by 78% and 35% respectively.

关键词

Keywords

references

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