基于魯棒H無窮濾波的步進電機轉(zhuǎn)子狀態(tài)估計
王超塵，楊濤
南京理工大學(xué) 自動化學(xué)院，江蘇 南京 210094
摘 要：為有效控制步進電機的運行，根據(jù)H 無窮魯棒濾波理論，設(shè)計了基于擴展H無窮濾波的步進電機狀態(tài)觀測器，并建立數(shù)學(xué)模型，將定子電流、轉(zhuǎn)子轉(zhuǎn)速和位置作為狀態(tài)變量。通過測量定子側(cè)的電流值和電壓值，利用擴展H 無窮濾波器對電機轉(zhuǎn)子的狀態(tài)做出最小方差估計。仿真結(jié)果表明，擴展H無窮濾波估算轉(zhuǎn)子轉(zhuǎn)速和位置信息是可行的，且擴展H無窮濾波精度和穩(wěn)定性都優(yōu)于擴展卡爾曼濾波。
關(guān)鍵詞：步進電機；擴展H無窮濾波；轉(zhuǎn)子轉(zhuǎn)速；轉(zhuǎn)子位置；無傳感器
中圖分類號：TM383.6 文獻標(biāo)識碼：A 文章編號：1007-3175(2014)02-0008-03
Rotor State Estimation of Step Motor Based on Robust H∞ Filter
WANG Chao-chen, YANG Tao
School of Automation, Nanjing University of Science and Technology, Nanjing 210094,China
Abstract: In order to control the operation of step motor effectively, the state observer of step motor was designed based on H∞ robust filter theory. The mathematical model of step motor was established and the stator current, rotor speed and rotor position were regarded as state vector. The H∞ filter can get the minimum variance estimation of rotor state by measuring stator current and voltage, and lay the foundation for the sensorless motor control. The experimental results show that the H∞ filter can estimate rotor velocity and position, and filtering accuracy and stability are better than extended Kalman filtering.
Key words: step motor; extended H∞ filter; rotor speed; rotor position; sensorless
參考文獻
[1] Chen H C, Liaw C M.Sensorless control via intelligent commutation tuning for brushless DC motor[J].IEE Proceedings Electric Power Applications, 1999，146(6)：678-684.
[2] Jeon Y S, Mok H S, Choe G H, et al.A new simulation model of BLDC motor with real back EMF waveform[C]//Proceeding from the 7th Workshop on Computers in Power Electronics, 2000.
[3] 付夢印.Kalman 濾波理論及其在導(dǎo)航系統(tǒng)中的應(yīng)用[M]. 北京：科學(xué)出版社，2003.
[4] Dan Simon.Optimal State Estimation：Kalman,H∞,and Nonlinear Approaches[M].Hoboken：John Wiley & Sons，2006.
[5] 楊韜儀，王輝，徐鋒. 兩相步進電動機細分方法研究[J]. 微電機，2007，40(9)：69-71.
[6] Einicke G A,White L B.Robust extended Kalman filtering[J].IEEE Transactions on Signal Processing, 1999，47(9)：2596-2599.
[7] Shaked U,Berman N.H∞ nonlinear filtering of discrete-time processes[J].IEEE Transactions on Signal Processing, 1995，43(9)：2205-2209.
