Multivariable bilinear subspace recursive likelihood identification for pumped storage motor

被引：0
|
作者：
Zhuang Xu [1 ,2 ]
Ge Bao-Jun [1 ]
Tao Dajun [1 ]
机构：
[1] Harbin Univ Sci & Technol, Harbin 150080, Heilongjiang, Peoples R China
[2] Northeast Dianli Univ, Jilin 132012, Jilin, Peoples R China
来源：
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS | 2019年 / 22卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Pumped storage motor; Multivariable; Bilinear; Subspace; Recursive likelihood identification; AUTOMATIC DETECTION; ENTROPY;
D O I：
10.1007/s10586-018-2066-6
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
To improve precision for model identification result of pumped storage motor, a kind of multivariable bilinear subspace recursive likelihood identification for pumped storage motor is put forward. Firstly, pumped storage motor magnetic filed equation is given, pumped storage motor model based on extension Kalman Filter is established, two-set identification models are constructed by coordination by utilizing two-group state vectors of resistance and inductance and two-set models work cooperatively to construct circulation identification algorithm; then, introduce subspace identification strategy, establish relevant data estimation equation by utilizing block Hankel matrix and realize valid identification to system parameter matrix by adopting least squares (LS); validity of proposed algorithm is verified by simulation experiment in matlab platform and hardware environment.
引用
收藏
页码：S4527 / S4533
页数：7
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