Torque ripple reduction in switched reluctance motor drives using B-spline neural networks

Zhengyu Lin; Donald S. Reay; Barry W. Williams; Xiangning He

doi:10.1109/TIA.2006.882671

Torque ripple reduction in switched reluctance motor drives using B-spline neural networks

Zhengyu Lin, Donald S. Reay, Barry W. Williams, Xiangning He

School of Engineering & Physical Sciences

Research output: Contribution to journal › Article › peer-review

60 Citations (Scopus)

Abstract

A switched reluctance motor torque ripple reduction scheme using a B-spline neural network (BSNN) is presented. Closed-loop torque control can be implemented using an on-line torque estimator. Due to the local weight updating algorithm used for the BSNN, an appropriate phase current profile for torque ripple reduction can be obtained on-line in real time. It has good dynamic performance with respect to changes in torque demand. The scheme does not require high-bandwidth current controllers. Simulation and experimental results demonstrate the validity of the scheme. © 2006 IEEE.

Original language	English
Pages (from-to)	1445-1453
Number of pages	9
Journal	IEEE Transactions on Industry Applications
Volume	42
Issue number	6
DOIs	https://doi.org/10.1109/TIA.2006.882671
Publication status	Published - Nov 2006

Keywords

Neural networks
Reluctance motors
Torque control

Access to Document

10.1109/TIA.2006.882671

Cite this

@article{1cd2b44e37a84bb89314e5189bd7dd3b,

title = "Torque ripple reduction in switched reluctance motor drives using B-spline neural networks",

abstract = "A switched reluctance motor torque ripple reduction scheme using a B-spline neural network (BSNN) is presented. Closed-loop torque control can be implemented using an on-line torque estimator. Due to the local weight updating algorithm used for the BSNN, an appropriate phase current profile for torque ripple reduction can be obtained on-line in real time. It has good dynamic performance with respect to changes in torque demand. The scheme does not require high-bandwidth current controllers. Simulation and experimental results demonstrate the validity of the scheme. {\textcopyright} 2006 IEEE.",

keywords = "Neural networks, Reluctance motors, Torque control",

author = "Zhengyu Lin and Reay, {Donald S.} and Williams, {Barry W.} and Xiangning He",

year = "2006",

month = nov,

doi = "10.1109/TIA.2006.882671",

language = "English",

volume = "42",

pages = "1445--1453",

journal = "IEEE Transactions on Industry Applications",

issn = "0093-9994",

publisher = "IEEE",

number = "6",

}

TY - JOUR

T1 - Torque ripple reduction in switched reluctance motor drives using B-spline neural networks

AU - Lin, Zhengyu

AU - Reay, Donald S.

AU - Williams, Barry W.

AU - He, Xiangning

PY - 2006/11

Y1 - 2006/11

N2 - A switched reluctance motor torque ripple reduction scheme using a B-spline neural network (BSNN) is presented. Closed-loop torque control can be implemented using an on-line torque estimator. Due to the local weight updating algorithm used for the BSNN, an appropriate phase current profile for torque ripple reduction can be obtained on-line in real time. It has good dynamic performance with respect to changes in torque demand. The scheme does not require high-bandwidth current controllers. Simulation and experimental results demonstrate the validity of the scheme. © 2006 IEEE.

AB - A switched reluctance motor torque ripple reduction scheme using a B-spline neural network (BSNN) is presented. Closed-loop torque control can be implemented using an on-line torque estimator. Due to the local weight updating algorithm used for the BSNN, an appropriate phase current profile for torque ripple reduction can be obtained on-line in real time. It has good dynamic performance with respect to changes in torque demand. The scheme does not require high-bandwidth current controllers. Simulation and experimental results demonstrate the validity of the scheme. © 2006 IEEE.

KW - Neural networks

KW - Reluctance motors

KW - Torque control

UR - http://www.scopus.com/inward/record.url?scp=37849189802&partnerID=8YFLogxK

U2 - 10.1109/TIA.2006.882671

DO - 10.1109/TIA.2006.882671

M3 - Article

SN - 0093-9994

VL - 42

SP - 1445

EP - 1453

JO - IEEE Transactions on Industry Applications

JF - IEEE Transactions on Industry Applications

IS - 6

ER -

Torque ripple reduction in switched reluctance motor drives using B-spline neural networks

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this