An improved stochastic gradient algorithm to identify PMSM parameters based on CAR models

Hui Jie Sun; Rui Qi Dong; Ying Zhang

doi:10.23919/ChiCC.2017.8027661

An improved stochastic gradient algorithm to identify PMSM parameters based on CAR models

Hui Jie Sun
, Rui Qi Dong^*
, Ying Zhang

^*Corresponding author for this work

Harbin Institute of Technology Shenzhen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

In this paper, we study the parameters identification problem of Permanent Magnet Synchronous Motor (PMSM) in steady state. First, the controlled auto-regressive (CAR) model of PMSM is established. Secondly, based on the obtained CAR model, an improved stochastic gradient algorithm is proposed to identify the electrical parameters of PMSM. By introducing a tuning parameter in the presented algorithm, the current estimation for the unknown PMSM parameters is updated by using the information not only in the current step but also in the previous step. In addition, a convergence result is provided for the developed algorithm. Finally, an example is given to show the advantage of the proposed algorithm for the parameters identification of PMSM.

Original language	English
Title of host publication	Proceedings of the 36th Chinese Control Conference, CCC 2017
Editors	Tao Liu, Qianchuan Zhao
Publisher	IEEE Computer Society
Pages	2076-2081
Number of pages	6
ISBN (Electronic)	9789881563934
DOIs	https://doi.org/10.23919/ChiCC.2017.8027661
State	Published - 7 Sep 2017
Externally published	Yes
Event	36th Chinese Control Conference, CCC 2017 - Dalian, China Duration: 26 Jul 2017 → 28 Jul 2017

Publication series

Name	Chinese Control Conference, CCC
ISSN (Print)	1934-1768
ISSN (Electronic)	2161-2927

Conference

Conference	36th Chinese Control Conference, CCC 2017
Country/Territory	China
City	Dalian
Period	26/07/17 → 28/07/17

Keywords

Convergence Analysis
PMSM
Parameter Identification
Stochastic Gradient Algorithm

Access to Document

10.23919/ChiCC.2017.8027661

Cite this

@inproceedings{c9e9c1f669a64571a3d2898e4addb56c,

title = "An improved stochastic gradient algorithm to identify PMSM parameters based on CAR models",

abstract = "In this paper, we study the parameters identification problem of Permanent Magnet Synchronous Motor (PMSM) in steady state. First, the controlled auto-regressive (CAR) model of PMSM is established. Secondly, based on the obtained CAR model, an improved stochastic gradient algorithm is proposed to identify the electrical parameters of PMSM. By introducing a tuning parameter in the presented algorithm, the current estimation for the unknown PMSM parameters is updated by using the information not only in the current step but also in the previous step. In addition, a convergence result is provided for the developed algorithm. Finally, an example is given to show the advantage of the proposed algorithm for the parameters identification of PMSM.",

keywords = "Convergence Analysis, PMSM, Parameter Identification, Stochastic Gradient Algorithm",

author = "Sun, \{Hui Jie\} and Dong, \{Rui Qi\} and Ying Zhang",

note = "Publisher Copyright: {\textcopyright} 2017 Technical Committee on Control Theory, CAA.; 36th Chinese Control Conference, CCC 2017 ; Conference date: 26-07-2017 Through 28-07-2017",

year = "2017",

month = sep,

day = "7",

doi = "10.23919/ChiCC.2017.8027661",

language = "英语",

series = "Chinese Control Conference, CCC",

publisher = "IEEE Computer Society",

pages = "2076--2081",

editor = "Tao Liu and Qianchuan Zhao",

booktitle = "Proceedings of the 36th Chinese Control Conference, CCC 2017",

address = "美国",

}

Sun, HJ, Dong, RQ & Zhang, Y 2017, An improved stochastic gradient algorithm to identify PMSM parameters based on CAR models. in T Liu & Q Zhao (eds), Proceedings of the 36th Chinese Control Conference, CCC 2017., 8027661, Chinese Control Conference, CCC, IEEE Computer Society, pp. 2076-2081, 36th Chinese Control Conference, CCC 2017, Dalian, China, 26/07/17. https://doi.org/10.23919/ChiCC.2017.8027661

An improved stochastic gradient algorithm to identify PMSM parameters based on CAR models. / Sun, Hui Jie; Dong, Rui Qi ; Zhang, Ying.
Proceedings of the 36th Chinese Control Conference, CCC 2017. ed. / Tao Liu; Qianchuan Zhao. IEEE Computer Society, 2017. p. 2076-2081 8027661 (Chinese Control Conference, CCC).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - An improved stochastic gradient algorithm to identify PMSM parameters based on CAR models

AU - Sun, Hui Jie

AU - Dong, Rui Qi

AU - Zhang, Ying

PY - 2017/9/7

Y1 - 2017/9/7

N2 - In this paper, we study the parameters identification problem of Permanent Magnet Synchronous Motor (PMSM) in steady state. First, the controlled auto-regressive (CAR) model of PMSM is established. Secondly, based on the obtained CAR model, an improved stochastic gradient algorithm is proposed to identify the electrical parameters of PMSM. By introducing a tuning parameter in the presented algorithm, the current estimation for the unknown PMSM parameters is updated by using the information not only in the current step but also in the previous step. In addition, a convergence result is provided for the developed algorithm. Finally, an example is given to show the advantage of the proposed algorithm for the parameters identification of PMSM.

AB - In this paper, we study the parameters identification problem of Permanent Magnet Synchronous Motor (PMSM) in steady state. First, the controlled auto-regressive (CAR) model of PMSM is established. Secondly, based on the obtained CAR model, an improved stochastic gradient algorithm is proposed to identify the electrical parameters of PMSM. By introducing a tuning parameter in the presented algorithm, the current estimation for the unknown PMSM parameters is updated by using the information not only in the current step but also in the previous step. In addition, a convergence result is provided for the developed algorithm. Finally, an example is given to show the advantage of the proposed algorithm for the parameters identification of PMSM.

KW - Convergence Analysis

KW - PMSM

KW - Parameter Identification

KW - Stochastic Gradient Algorithm

UR - https://www.scopus.com/pages/publications/85032205136

U2 - 10.23919/ChiCC.2017.8027661

DO - 10.23919/ChiCC.2017.8027661

M3 - 会议稿件

AN - SCOPUS:85032205136

T3 - Chinese Control Conference, CCC

SP - 2076

EP - 2081

BT - Proceedings of the 36th Chinese Control Conference, CCC 2017

A2 - Liu, Tao

A2 - Zhao, Qianchuan

PB - IEEE Computer Society

T2 - 36th Chinese Control Conference, CCC 2017

Y2 - 26 July 2017 through 28 July 2017

ER -

An improved stochastic gradient algorithm to identify PMSM parameters based on CAR models

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this