中国机械工程 ›› 2012, Vol. 23 ›› Issue (19): 2347-2350.

• 机械基础工程 • 上一篇    下一篇

挖掘臂动力学参数与液压缸摩擦力参数辨识

黎波;严骏;郭刚;钱海波;张梅军   

  1. 解放军理工大学,南京,210007
  • 出版日期:2012-10-10 发布日期:2012-10-17
  • 基金资助:
    国家自然科学基金资助项目(51175511)
    National Natural Science Foundation of China(No. 51175511)

#br# Parameter Identification of Dynamics Model for Excavator Arm and Friction Model for Cylinder

Li Bo;Yan Jun;Guo Gang;Qian Haibo;Zhang Meijun   

  1. PLA University of Science and Technology, Nanjing, 210007
  • Online:2012-10-10 Published:2012-10-17
  • Supported by:
    National Natural Science Foundation of China(No. 51175511)

摘要:

建立了挖掘臂单关节动力学模型及液压缸驱动力模型,将模型中的未知动力学参数及非线性摩擦力参数线性化表示。利用测量的系统压力及角度信息,分别采用带遗忘因子的递推最小二乘法及递推增广最小二乘法对系统参数进行辨识。对辨识所得的两个模型进行仿真,与实际系统对比分析结果表明,辨识模型能很好地逼近实际系统。误差对比分析结果表明:递推增广最小二乘法比带遗忘因子的递推最小二乘法误差减小约28%,对系统噪声有更好的鲁棒性。

关键词: 液压挖掘臂, 动力学, 非线性摩擦, 最小二乘法, 参数辨识

Abstract:

Dynamics model for a single excavator arm and a driving-force model for cylinder were established, unknown parameters for the dynamics and nonlinear friction were described by linear-in-parameter models. Based on the acquired pressure and angular data, forgetting factor recursive least square method and recursive extended least square method were adopted to identify the unknown parameters. Comparison results demonstrate that both identified models approximate to the actual system well. Comparing with the forgetting factor recursive least square method, the error of the recursive extended least square method is reduced by 28%, it is more robust to the system noise.

Key words: hydraulic excavator arm, dynamics, nonlinear friction, least square method, parameter identification

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