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水下装备关节电机多参数辨识研究

石麟 胡桥 石鑫东 孙良杰 张箭 刘海洋

水下无人系统学报2024,Vol.32Issue(6):1029-1038,10.
水下无人系统学报2024,Vol.32Issue(6):1029-1038,10.DOI:10.11993/j.issn.2096-3920.2024-0062

水下装备关节电机多参数辨识研究

Multi-parameter Identification of Underwater Equipment Joint Motor

石麟 1胡桥 2石鑫东 1孙良杰 1张箭 1刘海洋1

作者信息

  • 1. 西安交通大学机械工程学院,陕西 西安,710049
  • 2. 西安交通大学机械工程学院,陕西 西安,710049||西安交通大学陕西省智能机器人重点实验室,710049
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摘要

Abstract

With the rapid development of unmanned undersea systems,joint motors play an important role as the core driving devices of underwater robots,underwater manipulators,and other underwater equipment.In this paper,the on-line multi-parameter identification of an underwater joint motor is studied to solve the problem that the precision and stability of motor control are deteriorated due to the change of motor parameters under the influence of different working environments.Specifically,the method of increasing steady-state operating points is used to realize multi-parameter full rank identification.At the same time,to improve the accuracy and robustness of the identification method,this study investigates the feasibility of extended Kalman filter(EKF)and H∞filter(H-infinity filter,HIF)in the identification of motor parameters.Then a new joint estimation method based on adaptive EKF(AEKF)and adaptive HIF(AHIF)is proposed.Through simulation comparison,it is found that in parameter identification,the steady-state standard deviation of the proposed AEKF+AHIF joint estimation method is reduced by 84.7%compared with that of the AEKF method,and the accuracy is increased by 91.7%compared with that of the AHIF method.The joint estimation method can provide theoretical and technical support for the stable and efficient operation of underwater joint motors.

关键词

水下装备/关节电机/参数辨识/扩展卡尔曼滤波/H∞滤波

Key words

underwater equipment/joint motor/parameter identification/extended Kalman filter/H-infinity filter

分类

军事科技

引用本文复制引用

石麟,胡桥,石鑫东,孙良杰,张箭,刘海洋..水下装备关节电机多参数辨识研究[J].水下无人系统学报,2024,32(6):1029-1038,10.

基金项目

国家自然科学基金项目资助(52371337). (52371337)

水下无人系统学报

OACSTPCD

2096-3920

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