Online Identification of Parameters for PMSM Based on a Modified Artificial Bee Colony Algorithm

The variable step size least mean square (LMS) technology is integrated into the artificial bee colony (ABC) algorithm, which significantly improves the exploitation of ABC and accelerates the convergence rate. In addition, a new probability model of onlooker bees is designed to prevent the solution...

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Bibliographic Details
Published in2024 International Conference on Advanced Robotics and Mechatronics (ICARM) pp. 443 - 448
Main Authors Ren, Xing, Cao, Yuanchao, Guo, Qing, Wu, Guicheng, Long, Qiang, Ran, Mengfan
Format Conference Proceeding
LanguageEnglish
Published IEEE 08.07.2024
Subjects
Accuracy
Artificial bee colony algorithm
Convergence
Mechatronics
Optimization
Parameter estimation
Permanent magnet motors
Robots
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Summary:The variable step size least mean square (LMS) technology is integrated into the artificial bee colony (ABC) algorithm, which significantly improves the exploitation of ABC and accelerates the convergence rate. In addition, a new probability model of onlooker bees is designed to prevent the solutions from easily falling into the local optimum. The modified ABC is called LMSABC, and an online parameter identification method based on LMSABC for permanent magnet synchronous motor (PMSM) is proposed. The diversity of LMSABC first decreases and then increases, thus ensuring that the algorithm converges quickly in the early stage and maintains strong exploration in the later stage. The simulation comparison results with other similar algorithms indicate that the proposed method has the highest parameter identification accuracy and the fastest convergence rate.
ISSN:2993-4990
DOI:10.1109/ICARM62033.2024.10715955