水下装备关节电机多参数辨识研究  

Multi-parameter Identification of Underwater Equipment Joint Motor

作　　者：石麟 胡桥[1,2] 石鑫东 孙良杰 张箭 刘海洋 SHI Lin;HU Qiao;SHI Xindong;SUN Liangjie;ZHANG jian;LIU Haiyang(School of Mechanical Engineering,Xi’an Jiaotong University,Xi’an 710049,China;Shaanxi Key Laboratory of IntelligentRobots,Xi’an Jiaotong University,Xi’an 710049,China)

机构地区：[1]西安交通大学机械工程学院,陕西西安710049 [2]西安交通大学陕西省智能机器人重点实验室,710049

出　　处：《水下无人系统学报》2024年第6期1029-1038,共10页Journal of Unmanned Undersea Systems

基　　金：国家自然科学基金项目资助(52371337).

摘　　要：随着水下无人系统的快速发展,关节电机作为水下机器人、水下机械臂等水下装备的核心驱动装置发挥着重要的作用。文中针对不同工作环境影响下导致的关节电机参数改变,从而引起的电机控制的精确性和稳定性变差的问题,开展电机多参数在线辨识研究。采用增加稳态工作点方法实现多参数的满秩辨识。同时,为提高辨识方法的精度和鲁棒性,研究了扩展卡尔曼滤波(EKF)和H_(∞)滤波(HIF)算法在电机参数辨识方面的可行性,进而提出了一种基于自适应EKF(AEKF)和自适应HIF(AHIF)的联合估计方法。通过仿真对比发现,在参数辨识时,所提出的AEKF+AHIF联合估计方法相较于AEKF算法稳态标准差最大减少了84.7%,相较于AHIF算法精确度最大提升了91.7%。该联合估计方法可为水下装备关节电机的稳定高效运行提供理论和技术支撑。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 

分 类 号：TJ630.32[兵器科学与技术—武器系统与运用工程] U674[交通运输工程—船舶及航道工程]