機器人負載的動力學參數辨識

張鐵; 覃彬彬; 鄒焱飚

doi:10.13374/j.issn2095-9389.2017.12.018

機器人負載的動力學參數辨識

doi: 10.13374/j.issn2095-9389.2017.12.018

華南理工大學機械與汽車工程學院, 廣州 510641

基金項目:

國家高檔數控機床與基礎制造裝備科技重大專項資助項目（2015ZX04005006）；廣東省科技重大專項資助項目（2014B090921004，2014B090920001）；廣州市科技重大專項資助項目（20160404009）

詳細信息

中圖分類號: TP242.2
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- 文章訪問數: 915
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出版歷程
- 收稿日期: 2017-02-17

Identification methods for robot payload dynamical parameters

School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510641, China

摘要

摘要: 為解決機器人末端負載的時變性給高速運動的機器人帶來控制精度降低的問題，研究了參數差值法、力矩求解法、全局參數辨識法的機器人末端負載動力學參數辨識的方法，以提高末端負載的辨識精度.得到的負載動力學參數用于動力學控制以提高機器人動態精度.通過建立拉格朗日動力學線性辨識模型，以最優激勵軌跡進行實時數據采集，采樣數據經過低通濾波及中心差分的處理后，代入相應的負載辨識方程式，并用加權最小二乘法解決線性方程組，可辨識到不同負載的動力學參數.實驗驗證了負載辨識方法的可行性.
- 機器人負載 /
- 動力學 /
- 線性模型 /
- 激勵軌跡 /
- 辨識 /
- 負載參數
Abstract: To solve the problem of low precision control in high speed motion robots due to a time-varying payload and to improve the identification accuracy of the payload, the dynamical parameter identification methods for robot end payload were studied. These methods included the parameter difference method, the moment method, and the global parameter identification method. The parameters were used to improve the dynamic precision in robot dynamic control. The dynamical parameters for different payloads can be identified with the Lagrange dynamic linear identification model, which acquires real-time data using the optimal incentive path and solves the equations by using the least square weight algorithm after the sample data was processed with a low-pass filter and central difference processes. The feasibility of the method was verified by experiments.
- robot payload /
- dynamic /
- linear model /
- incentive path /
- identification /
- payload p

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參考文獻(13)

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