Chaotic whale optimizer variants for parameters estimation of the chaotic behavior in Permanent Magnet Synchronous Motor

Permanent Magnet Synchronous Motor (PMSM) is widely used in the industrial applications because of its simple construction and its high efficiency. Unfortunately, if a small change has occurred in the system parameters, the PMSM displays an unexpected performance which is known as a chaotic behavior...

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Bibliographic Details
Published in:Applied soft computing Vol. 74; pp. 479 - 503
Main Authors: Yousri, Dalia, Allam, Dalia, Eteiba, M.B.
Format: Journal Article
Language:English
Published: Elsevier B.V 01.01.2019
Subjects:
Chaos maps
Chaotic system
Chaotic whale optimizer algorithm
Parameters estimation
Permanent magnet synchronous motor
Whale optimizer algorithm
Chaos maps
Whale optimizer algorithm
Permanent magnet synchronous motor
Parameters estimation
Chaotic system
Chaotic whale optimizer algorithm
ISSN:1568-4946, 1872-9681
Online Access:Get full text
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Summary:Permanent Magnet Synchronous Motor (PMSM) is widely used in the industrial applications because of its simple construction and its high efficiency. Unfortunately, if a small change has occurred in the system parameters, the PMSM displays an unexpected performance which is known as a chaotic behavior. To control this undesirable behavior, it is crucial to propose a robust tool to extract the model parameters accurately and rapidly. In this work, novel developed optimization techniques called Chaotic Whale Optimization variants (CWOA) are proposed where the standard Whale Optimization Algorithm (WOA) is integrated with different ten chaos maps to tune some of its parameters. Four CWOA variants are introduced, tested and validated mathematically over CEC 2017. In addition, CWOA variants and the standard WOA version are proposed to estimate the parameters of the chaotic behavior in PMSM at both of the off-line and the on-line operating conditions without and with noise. The results of the proposed algorithms are compared with that of the previous techniques in literature to test their efficiency, reliability, and accuracy. An intensive statistical analysis is accomplished for extra validation of the superiority of the proposed variants. The overall results indicate that the CWOA-II variant with the logistic chaos map offers the best performance among all other variants where it provides lower error values between the estimated and the original system performance, higher convergence speed and shorter execution time. This eventually helps to provide an accurate and fast description of the chaotic region to ensure a fast control of the motor as well as a fast protection from damage. •Four Chaotic Whale Optimization variants (CWOA) are introduced.•CWOA variants are applied on a complex engineering application.•CWOA estimate the parameters of chaotic behavior in PMSM.•Results of CWOA variants are compared with that of the WOA and the publish algorithms in literature.•Chaos maps improve the performance of the original Whale Optimization Algorithm.
ISSN:1568-4946
1872-9681
DOI:10.1016/j.asoc.2018.10.032