Real-time on-line parameter estimation of linear switched reluctance motor

Chow Norbert Cheung; J. F. Pan; Jin Quan Li

doi:10.1109/ICELMACH.2010.5607902

Real-time on-line parameter estimation of linear switched reluctance motor

Chow Norbert Cheung, J. F. Pan, Jin Quan Li

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

2 Citations (Scopus)

Abstract

The on-line least-square identification method is applied for the linear switched reluctance motor (LSRM) based closed-loop control system. Since switched reluctance motors have severe nonlinear characteristics, on-line system identification for model parameters is the basis for precise modeling and effective control algorithms. By on-line parameter identification of LSRM with least-square scheme, the parameter characteristics can be predicted despite of operation variations. The experimental results demonstrate the identification scheme has fast response and converging speed and the capability of effective parameter prediction under different conditions.

Original language	English
Title of host publication	19th International Conference on Electrical Machines, ICEM 2010
DOIs	https://doi.org/10.1109/ICELMACH.2010.5607902
Publication status	Published - 6 Dec 2010
Event	19th International Conference on Electrical Machines, ICEM 2010 - Rome, Italy Duration: 6 Sept 2010 → 8 Sept 2010

Conference

Conference	19th International Conference on Electrical Machines, ICEM 2010
Country/Territory	Italy
City	Rome
Period	6/09/10 → 8/09/10

Keywords

dSPACE 1104
Least-square
LSRM
On-line identification
Parameter convergence
PD controller
Switched reluctance

ASJC Scopus subject areas

Electrical and Electronic Engineering
Mechanical Engineering

More information

10.1109/ICELMACH.2010.5607902

Cite this

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title = "Real-time on-line parameter estimation of linear switched reluctance motor",

abstract = "The on-line least-square identification method is applied for the linear switched reluctance motor (LSRM) based closed-loop control system. Since switched reluctance motors have severe nonlinear characteristics, on-line system identification for model parameters is the basis for precise modeling and effective control algorithms. By on-line parameter identification of LSRM with least-square scheme, the parameter characteristics can be predicted despite of operation variations. The experimental results demonstrate the identification scheme has fast response and converging speed and the capability of effective parameter prediction under different conditions.",

keywords = "dSPACE 1104, Least-square, LSRM, On-line identification, Parameter convergence, PD controller, Switched reluctance",

author = "Cheung, {Chow Norbert} and Pan, {J. F.} and Li, {Jin Quan}",

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doi = "10.1109/ICELMACH.2010.5607902",

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T1 - Real-time on-line parameter estimation of linear switched reluctance motor

AU - Cheung, Chow Norbert

AU - Pan, J. F.

AU - Li, Jin Quan

PY - 2010/12/6

Y1 - 2010/12/6

N2 - The on-line least-square identification method is applied for the linear switched reluctance motor (LSRM) based closed-loop control system. Since switched reluctance motors have severe nonlinear characteristics, on-line system identification for model parameters is the basis for precise modeling and effective control algorithms. By on-line parameter identification of LSRM with least-square scheme, the parameter characteristics can be predicted despite of operation variations. The experimental results demonstrate the identification scheme has fast response and converging speed and the capability of effective parameter prediction under different conditions.

AB - The on-line least-square identification method is applied for the linear switched reluctance motor (LSRM) based closed-loop control system. Since switched reluctance motors have severe nonlinear characteristics, on-line system identification for model parameters is the basis for precise modeling and effective control algorithms. By on-line parameter identification of LSRM with least-square scheme, the parameter characteristics can be predicted despite of operation variations. The experimental results demonstrate the identification scheme has fast response and converging speed and the capability of effective parameter prediction under different conditions.

KW - dSPACE 1104

KW - Least-square

KW - LSRM

KW - On-line identification

KW - Parameter convergence

KW - PD controller

KW - Switched reluctance

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U2 - 10.1109/ICELMACH.2010.5607902

DO - 10.1109/ICELMACH.2010.5607902

M3 - Conference article published in proceeding or book

SN - 9781424441754

BT - 19th International Conference on Electrical Machines, ICEM 2010

T2 - 19th International Conference on Electrical Machines, ICEM 2010

Y2 - 6 September 2010 through 8 September 2010

ER -

Real-time on-line parameter estimation of linear switched reluctance motor

Abstract

Conference

Keywords

ASJC Scopus subject areas

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