Novel topologies for identification and control of PMSM using artificial neural network

Rajesh Kumar; R. A. Gupta; Ajay Kr Bansal

doi:10.1049/ic:20070590

Novel topologies for identification and control of PMSM using artificial neural network

Rajesh Kumar
, R. A. Gupta
, Ajay Kr Bansal

Malaviya National Institute of Technology

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

3 Citations (Scopus)

Abstract

Rotor speed and performance of permanent magnet synchronous motor (PMSM) suffers from accuracy due to variation of motor parameters such as stator resistance, stator inductance or torque constant. The conventional linear estimators are not adaptive. Neural networks (ANN) have shown better results when estimating or controlling nonlinear systems. In this paper an artificial neural network based high performance speed control system for a PMSM with different topologies and their performance comparison is presented. The main purpose is to achieve accurate trajectory control of the speed, when the motor and load parameters are unknown. The PMSM motor was identified using three different topologies (speed, voltage and current). The unknown nonlinear dynamics of the motor and the load are captured by the ANN. The performance of the identification and control algorithm are evaluated by simulating them on a typical PMSM motor model.

Original language	English
Title of host publication	IET-UK International Conference on Information and Communication Technology in Electrical Sciences, ICTES 2007
Pages	75-80
Number of pages	6
Edition	2
DOIs	https://doi.org/10.1049/ic:20070590
Publication status	Published - 2007
Externally published	Yes
Event	IET-UK International Conference on Information and Communication Technology in Electrical Sciences, ICTES 2007 - Tamil Nadu, India Duration: 20 Dec 2007 → 22 Dec 2007

Publication series

Name	IET Seminar Digest
Number	2
Volume	2007

Conference

Conference	IET-UK International Conference on Information and Communication Technology in Electrical Sciences, ICTES 2007
Country/Territory	India
City	Tamil Nadu
Period	20/12/07 → 22/12/07

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Artificial neural network
Back - propagation ANN
PMSM
System identification

ASJC Scopus subject areas

Electrical and Electronic Engineering

Access to Document

10.1049/ic:20070590

Cite this

@inproceedings{65ca232e93034adc9040ea3badc294ab,

title = "Novel topologies for identification and control of PMSM using artificial neural network",

abstract = "Rotor speed and performance of permanent magnet synchronous motor (PMSM) suffers from accuracy due to variation of motor parameters such as stator resistance, stator inductance or torque constant. The conventional linear estimators are not adaptive. Neural networks (ANN) have shown better results when estimating or controlling nonlinear systems. In this paper an artificial neural network based high performance speed control system for a PMSM with different topologies and their performance comparison is presented. The main purpose is to achieve accurate trajectory control of the speed, when the motor and load parameters are unknown. The PMSM motor was identified using three different topologies (speed, voltage and current). The unknown nonlinear dynamics of the motor and the load are captured by the ANN. The performance of the identification and control algorithm are evaluated by simulating them on a typical PMSM motor model.",

keywords = "Artificial neural network, Back - propagation ANN, PMSM, System identification",

author = "Rajesh Kumar and Gupta, \{R. A.\} and Bansal, \{Ajay Kr\}",

year = "2007",

doi = "10.1049/ic:20070590",

language = "English",

isbn = "9780863419379",

series = "IET Seminar Digest",

number = "2",

pages = "75--80",

booktitle = "IET-UK International Conference on Information and Communication Technology in Electrical Sciences, ICTES 2007",

edition = "2",

note = "IET-UK International Conference on Information and Communication Technology in Electrical Sciences, ICTES 2007 ; Conference date: 20-12-2007 Through 22-12-2007",

}

Kumar, R, Gupta, RA & Bansal, AK 2007, Novel topologies for identification and control of PMSM using artificial neural network. in IET-UK International Conference on Information and Communication Technology in Electrical Sciences, ICTES 2007. 2 edn, IET Seminar Digest, no. 2, vol. 2007, pp. 75-80, IET-UK International Conference on Information and Communication Technology in Electrical Sciences, ICTES 2007, Tamil Nadu, India, 20/12/07. https://doi.org/10.1049/ic:20070590

Novel topologies for identification and control of PMSM using artificial neural network. / Kumar, Rajesh; Gupta, R. A.; Bansal, Ajay Kr.
IET-UK International Conference on Information and Communication Technology in Electrical Sciences, ICTES 2007. 2. ed. 2007. p. 75-80 (IET Seminar Digest; Vol. 2007, No. 2).

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

TY - GEN

T1 - Novel topologies for identification and control of PMSM using artificial neural network

AU - Kumar, Rajesh

AU - Gupta, R. A.

AU - Bansal, Ajay Kr

PY - 2007

Y1 - 2007

N2 - Rotor speed and performance of permanent magnet synchronous motor (PMSM) suffers from accuracy due to variation of motor parameters such as stator resistance, stator inductance or torque constant. The conventional linear estimators are not adaptive. Neural networks (ANN) have shown better results when estimating or controlling nonlinear systems. In this paper an artificial neural network based high performance speed control system for a PMSM with different topologies and their performance comparison is presented. The main purpose is to achieve accurate trajectory control of the speed, when the motor and load parameters are unknown. The PMSM motor was identified using three different topologies (speed, voltage and current). The unknown nonlinear dynamics of the motor and the load are captured by the ANN. The performance of the identification and control algorithm are evaluated by simulating them on a typical PMSM motor model.

AB - Rotor speed and performance of permanent magnet synchronous motor (PMSM) suffers from accuracy due to variation of motor parameters such as stator resistance, stator inductance or torque constant. The conventional linear estimators are not adaptive. Neural networks (ANN) have shown better results when estimating or controlling nonlinear systems. In this paper an artificial neural network based high performance speed control system for a PMSM with different topologies and their performance comparison is presented. The main purpose is to achieve accurate trajectory control of the speed, when the motor and load parameters are unknown. The PMSM motor was identified using three different topologies (speed, voltage and current). The unknown nonlinear dynamics of the motor and the load are captured by the ANN. The performance of the identification and control algorithm are evaluated by simulating them on a typical PMSM motor model.

KW - Artificial neural network

KW - Back - propagation ANN

KW - PMSM

KW - System identification

UR - https://www.scopus.com/pages/publications/67650456464

U2 - 10.1049/ic:20070590

DO - 10.1049/ic:20070590

M3 - Conference contribution

AN - SCOPUS:67650456464

SN - 9780863419379

T3 - IET Seminar Digest

SP - 75

EP - 80

BT - IET-UK International Conference on Information and Communication Technology in Electrical Sciences, ICTES 2007

T2 - IET-UK International Conference on Information and Communication Technology in Electrical Sciences, ICTES 2007

Y2 - 20 December 2007 through 22 December 2007

ER -

Novel topologies for identification and control of PMSM using artificial neural network

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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