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液壓挖掘臂二自由度動力學(xué)參數(shù)辨識
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國家自然科學(xué)基金資助項目（51175511）


2-DOF Dynamic Parameters Identification for Hydraulic Excavator Arm
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    摘要:

    通過拉格朗日法建立了斗桿、鏟斗的二自由度動力學(xué)模型,，并將系統(tǒng)動力學(xué)模型整理為未知組合參數(shù)的線性化表示,。通過對擬合的關(guān)節(jié)角-液壓缸位移函數(shù)進(jìn)行求導(dǎo)得到關(guān)節(jié)力矩與液壓缸驅(qū)動力間的函數(shù)關(guān)系,，并在液壓缸驅(qū)動力模型中引入摩擦力,。分別采用遞推最小二乘法與遞推隨機(jī)牛頓法對系統(tǒng)動力學(xué)模型的未知參數(shù)進(jìn)行辨識,。將辨識所得模型用于預(yù)測驅(qū)動力矩,，與實(shí)測數(shù)據(jù)對比分析表明,，隨機(jī)牛頓法比最小二乘法的預(yù)測誤差在斗桿與鏟斗關(guān)節(jié)分別減少約65%和63%,。結(jié)論表明隨機(jī)牛頓法對系統(tǒng)噪聲的魯棒性更好,，能獲得系統(tǒng)精確的動力學(xué)模型。

    Abstract:

    The 2-DOF dynamic model of these two joint was built by using Euler-Lagrange formulation. It was simplified to a linear-in-parameter mode. The relationship between joint torque and actuator force was deduced by differentiating the function of relationship between the joint angle and cylinder displacement, and friction was introduced into the actuator force. The recursive least square method (RLS) and recursive stochastic Newton algorithm (RSNA) were used to identify the unknown combination parameters respectively. Comparison experiments showed the predictive errors of joint torque of RSNA was reduced by 65% and 63% for the dipper joint and bucket joint respectively. The results demonstrated RSNA was more robust to the system noise. It can identify the dynamic parameters precisely. 

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嚴(yán)駿,黎波,郭剛,唐建,張梅軍.液壓挖掘臂二自由度動力學(xué)參數(shù)辨識[J].農(nóng)業(yè)機(jī)械學(xué)報,2013,44(2):17-21. Yan Jun, Li Bo, Guo Gang, Tang Jian, Zhang Meijun.2-DOF Dynamic Parameters Identification for Hydraulic Excavator Arm[J]. Transactions of the Chinese Society for Agricultural Machinery,2013,44(2):17-21.

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  • 在線發(fā)布日期: 2013-02-04
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