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Genetic algorithm optimized robust nonlinear observer for a wind turbine system based on permanent magnet synchronous generator. / Mansouri, Mohamed ; Bey, Mohamed; Hassaine, Said; Larbi, Mhamed; Allaoui, Tayeb; Denai, Mouloud.

In: ISA Transactions, 10.02.2022.

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@article{bffc2117abf145c586677a7e6f2abb4c,
title = "Genetic algorithm optimized robust nonlinear observer for a wind turbine system based on permanent magnet synchronous generator",
abstract = "This paper presents an optimal control scheme for a Permanent Magnet Synchronous Generator (PMSG) coupled to a wind turbine operating without a position sensor. This sensorless scheme includes two observers: The first observer uses the flux to estimate the speed. However, an increase in the temperature or a degradation of the permanent magnet characteristics will result in a demagnetization of the machine causing a drop in the flux. The second observer is therefore used to estimate these changes in the flux from the speed and guaranties the stability of the system. This structure leads to a better exchange of information between the two observers, eliminates the problem of encoder and compensates for the demagnetization problem. To improve the precision of the speed estimator, the gain of the non-linear observer is optimized using Genetic Algorithm (GA) and the speed is obtained from a modified Phase Locked Loop (PLL) method using an optimized Sliding Mode Controller (SMC). Furthermore, to enhance the convergence speed of this observer scheme and improve the performance of the system a Fast Super Twisting Sliding Mode Control (FSTSMC) is introduced to reinforce the SMC strategy. A series of simulations are presented to show the effectiveness and robustness of proposed observer scheme.",
keywords = "Fast super twisting sliding mode control, Genetic algorithm, Non-salient pole PMSG, PLL, Sensorless control, Wind turbine",
author = "Mohamed Mansouri and Mohamed Bey and Said Hassaine and Mhamed Larbi and Tayeb Allaoui and Mouloud Denai",
note = "{\textcopyright} 2022 ISA. Published by Elsevier Ltd. All rights reserved. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1016/j.isatra.2022.02.004",
year = "2022",
month = feb,
day = "10",
doi = "10.1016/j.isatra.2022.02.004",
language = "English",
journal = "ISA Transactions",
issn = "0019-0578",
publisher = "ISA - Instrumentation, Systems, and Automation Society",

}

RIS

TY - JOUR

T1 - Genetic algorithm optimized robust nonlinear observer for a wind turbine system based on permanent magnet synchronous generator

AU - Mansouri, Mohamed

AU - Bey, Mohamed

AU - Hassaine, Said

AU - Larbi, Mhamed

AU - Allaoui, Tayeb

AU - Denai, Mouloud

N1 - © 2022 ISA. Published by Elsevier Ltd. All rights reserved. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1016/j.isatra.2022.02.004

PY - 2022/2/10

Y1 - 2022/2/10

N2 - This paper presents an optimal control scheme for a Permanent Magnet Synchronous Generator (PMSG) coupled to a wind turbine operating without a position sensor. This sensorless scheme includes two observers: The first observer uses the flux to estimate the speed. However, an increase in the temperature or a degradation of the permanent magnet characteristics will result in a demagnetization of the machine causing a drop in the flux. The second observer is therefore used to estimate these changes in the flux from the speed and guaranties the stability of the system. This structure leads to a better exchange of information between the two observers, eliminates the problem of encoder and compensates for the demagnetization problem. To improve the precision of the speed estimator, the gain of the non-linear observer is optimized using Genetic Algorithm (GA) and the speed is obtained from a modified Phase Locked Loop (PLL) method using an optimized Sliding Mode Controller (SMC). Furthermore, to enhance the convergence speed of this observer scheme and improve the performance of the system a Fast Super Twisting Sliding Mode Control (FSTSMC) is introduced to reinforce the SMC strategy. A series of simulations are presented to show the effectiveness and robustness of proposed observer scheme.

AB - This paper presents an optimal control scheme for a Permanent Magnet Synchronous Generator (PMSG) coupled to a wind turbine operating without a position sensor. This sensorless scheme includes two observers: The first observer uses the flux to estimate the speed. However, an increase in the temperature or a degradation of the permanent magnet characteristics will result in a demagnetization of the machine causing a drop in the flux. The second observer is therefore used to estimate these changes in the flux from the speed and guaranties the stability of the system. This structure leads to a better exchange of information between the two observers, eliminates the problem of encoder and compensates for the demagnetization problem. To improve the precision of the speed estimator, the gain of the non-linear observer is optimized using Genetic Algorithm (GA) and the speed is obtained from a modified Phase Locked Loop (PLL) method using an optimized Sliding Mode Controller (SMC). Furthermore, to enhance the convergence speed of this observer scheme and improve the performance of the system a Fast Super Twisting Sliding Mode Control (FSTSMC) is introduced to reinforce the SMC strategy. A series of simulations are presented to show the effectiveness and robustness of proposed observer scheme.

KW - Fast super twisting sliding mode control

KW - Genetic algorithm

KW - Non-salient pole PMSG

KW - PLL

KW - Sensorless control

KW - Wind turbine

UR - http://www.scopus.com/inward/record.url?scp=85125343308&partnerID=8YFLogxK

U2 - 10.1016/j.isatra.2022.02.004

DO - 10.1016/j.isatra.2022.02.004

M3 - Article

JO - ISA Transactions

JF - ISA Transactions

SN - 0019-0578

ER -