Proceedings of the 2nd International Conference On Systems Engineering and Modeling (ICSEM 2013)

Chaotic Ant Swarm Based Parameter Estimation of Induction Motor from Manufacturer Data

Authors
Yan-jie Li, Zhu-zhi Jia
Corresponding Author
Yan-jie Li
Available Online April 2013.
DOI
10.2991/icsem.2013.40How to use a DOI?
Keywords
Chaotic Ant Swarm Algorithm, Induction Motor, Parameter Estimation
Abstract

A method of parameter estimation of induction motor based on optimization using a chaotic swarm algorithm is presented. The parameter estimation methodology describes a method for estimating the steady-state equivalent circuit parameters from the motor performance characteristic, which is normally available from manufacturer data or from tests. The optimization problem is formulated as multi-objective function to minimize the error between the estimated and the manufacturer data. Chaotic ant swarm algorithm is a novel optimization method, which has the ability of global optimum search. A numerical simulation on the test motor is conducted. Simulation results show that the proposed method is effective in parameter estimation of the induction motor.

Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd International Conference On Systems Engineering and Modeling (ICSEM 2013)
Series
Advances in Intelligent Systems Research
Publication Date
April 2013
ISBN
10.2991/icsem.2013.40
ISSN
1951-6851
DOI
10.2991/icsem.2013.40How to use a DOI?
Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yan-jie Li
AU  - Zhu-zhi Jia
PY  - 2013/04
DA  - 2013/04
TI  - Chaotic Ant Swarm Based Parameter Estimation of Induction Motor from Manufacturer Data
BT  - Proceedings of the 2nd International Conference On Systems Engineering and Modeling (ICSEM 2013)
PB  - Atlantis Press
SP  - 200
EP  - 204
SN  - 1951-6851
UR  - https://doi.org/10.2991/icsem.2013.40
DO  - 10.2991/icsem.2013.40
ID  - Li2013/04
ER  -