宇航学报

宇航学报 ›› 2016, Vol. 37 ›› Issue (10): 1215-1221.doi: 10.3873/j.issn.1000-1328.2016.10.009

• 制导、导航与控制 • 上一篇    下一篇

带有触觉的空间机械臂操控未知载荷特性识别

侯月阳，卢山，于学文，王奉文   

  1. 1. 上海航天控制技术研究所，上海201109；2. 上海市空间智能控制技术重点实验室，上海201109
  • 收稿日期:2016-02-24 修回日期:2016-04-06 出版日期:2016-10-15 发布日期:2016-10-25
  • 基金资助:

    上海市科技人才计划（14XD1421500）；上海市自然科学基金（16ZR1415600）

Characteristic Identification of Unknown Load Controlled by Space Manipulator Based on Tactile

HOU Yue yang, LU Shan, YU Xue wen, WANG Feng wen   

  1. 1. Shanghai Aerospace Control Technology Institute, Shanghai 201109, China;
     2. Shanghai Key Laboratory of Aerospace Intelligent Control Technology, Shanghai 201109, China
  • Received:2016-02-24 Revised:2016-04-06 Online:2016-10-15 Published:2016-10-25

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摘要：

为在线准确辨识载荷特性参数，提出一种利用关节力矩和触觉传感信息进行未知载荷特性参数辨识的方法。该方法基于牛顿-欧拉方程，采用归一化最小均方误差法进行自适应滤波，从而辨识出未知载荷的特性参数。为校验算法，利用MATLAB/Simulink和ADAMS软件搭建未知载荷特性辨识仿真平台。该平台执行机构包括多自由度机械臂和二指爪末端操作器，机械臂关节具有力矩传感，末端操作器指爪内侧具有触力传感器。仿真表明，在具有激励信号幅值1 %的白噪声情况下，辨识误差小于2 %。

关键词: 空间机械臂, 特性辨识, 未知载荷, 触觉传感, 归一化最小均方误差法

Abstract:

In order to accurately identify the load parameters online, a method is proposed, in which the tactile sensor information of an end-effector is used to identify the characteristic parameters of an unknown load. The method is based on the Newton-Euler equations and using the normalized least mean square error method adaptive filtering. The software of MATLAB/Simulink and ADAMS is used to build the unknown load parameters identification simulation platform in order to verify the algorithm. The actuating mechanism of the simulation platform includes a multi-DOF space manipulator and an end-effector with two claws. The manipulator arm joints have torque sensors. The inner end of the claws for the end-effector each has a tactile sensor, whose data is used to obtain the characteristic parameters. The simulation shows that the identification error is less 2% with the white noise whose values reach to 1% of the excitation signal ranges.

Key words: Space manipulator, Characteristic identification, Unknown load, Tactile sensing, Normalized least mean square error method

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