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兵工学报 ›› 2012, Vol. 33 ›› Issue (12): 1527-1532.doi: 10.3969/j.issn.1000-1093.2012.12.020

• 论文 • 上一篇    下一篇

基于Hammerstein模型的挖掘臂伺服系统参数辨识

严骏1,黎波1,郭刚1, 曾拥华1,彭卓2,张梅军1   

  1. (1.解放军理工大学 野战工程学院, 江苏 南京 210007; 2.总装备部 通用装备保障部, 北京 100720)
  • 收稿日期:2011-04-28 修回日期:2011-04-28 上线日期:2014-01-09
  • 作者简介:严骏(1962—),男,教授,博士生导师
  • 基金资助:
    国家自然科学基金项目(51175511)

Parameter Identification of Servo System for Excavator Arm Based on Hammerstein Model

YAN Jun1, LI Bo1, GUO Gang1, ZENG Yong-hua1, PENG Zhuo2, ZHANG Mei-jun1   

  1. (1. College of Field Engineers, PLA University of Science and Technology, Nanjing 210007, Jiangsu, China;2.The Department of General Equipment Supporting Chief, Equipment Staff, Beijing 100720, China)
  • Received:2011-04-28 Revised:2011-04-28 Online:2014-01-09

摘要: 液压挖掘臂伺服系统是复杂非线性系统,针对线性模型难以准确反映系统动态的特性,采用包含静态非线性模块和动态线性模块的Hammerstein模型来描述该系统。Hammerstein模型中的线性模块采用离散自回归模型(ARX),非线性模块则采用分段多项式基函数。利用多频率正弦激励与角度输出信号,采用带遗忘因子的递推最小二乘法实现线性与非线性模块参数的解耦辨识。通过对比实验分析辨识所得Hammerstein模型与ARX模型,得Hammerstein模型误差比线性模型误差减小约77%,结论表明采用Hammerstein模型描述挖掘臂伺服系统是有效可行的。

关键词: 机械电子工程, 电液伺服系统, Hammerstein模型, 递推最小二乘法, 非线性辨识

Abstract: According to the complex nonlinear properties of hydraulic excavator arm’s servo system, a Hammerstein model which contains static nonlinearity and dynamic linearity was adopted to describe the system instead of linear model. The dynamic linear module was described by a discrete AutoRegressive eXogeneous (ARX) model, and the static nonlinearity module was described by a twosegment polynomial. The forgetting factor recursive least square method was applied to realize decomposition identification of the parameters for both linear and nonlinear module through multifrequency sinusoidal input and angle output signal. The comparison experiments between the identified Hammerstein model and ARX model indicated that the error of Hammerstein model was reduced by 77%, the results demonstrated that Hammerstein model meets the need for describing the servo system of excavator arm.

Key words: mechatronics engineering, electrohydraulic servo system, Hammerstein model, recursive
least square method,
nonlinear identification

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