Application of Simulated Annealing Particle Swarm Optimization Based on Correlation in Parameter Identification of Induction Motor
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-07-08
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
The strengths and weaknesses of correlation algorithm, simulated annealing algorithm, and particle swarm optimization algorithm are studied in this paper.
A hybrid optimization algorithm is proposed by drawing upon the three algorithms, and the specific application processes are given.
To extract the current fundamental signal, the correlation algorithm is used.
To identify the motor dynamic parameter, the filtered stator current signal is simulated using simulated annealing particle swarm algorithm.
The simulated annealing particle swarm optimization algorithm effectively incorporates the global optimization ability of simulated annealing algorithm with the fast convergence of particle swarm optimization by comparing the identification results of asynchronous motor with constant torque load and step load.
American Psychological Association (APA)
Wang, Lei& Liu, Yong-Qiang. 2018. Application of Simulated Annealing Particle Swarm Optimization Based on Correlation in Parameter Identification of Induction Motor. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1205884
Modern Language Association (MLA)
Wang, Lei& Liu, Yong-Qiang. Application of Simulated Annealing Particle Swarm Optimization Based on Correlation in Parameter Identification of Induction Motor. Mathematical Problems in Engineering No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1205884
American Medical Association (AMA)
Wang, Lei& Liu, Yong-Qiang. Application of Simulated Annealing Particle Swarm Optimization Based on Correlation in Parameter Identification of Induction Motor. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1205884
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1205884