Optimisation of Model Predictive Torque Control Strategy with Standard and Multi-Objective Genetic Algorithms

• Autorzy: Zerdali Emrah , Gurel Aycan
• Języki publikacji: EN

Abstrakty

EN

In this paper, the flux error-related weighting factor (WF) of the predictive torque control (PTC) strategy for induction motor (IM) control is optimised by a standard genetic algorithm (SGA) through speed errors only and multi-objective genetic algorithm (MOGA) through torque and flux errors. This paper compares the performances of both optimisation methods. Compared to MOGA, SGA offers a straightforward way to select WF and does not need a decision-making method to choose a final solution. But MOGA considers the given problem in a multi-objective way and directly optimises the control objectives of the PTC strategy. Comparisons are made over the flux and torque ripples, total harmonic distortion of stator phase current, and average switching frequency for different operating conditions. Simulation results show that both methods choose a close WF value. Consequently, SGA stands out in the optimisation of the PTC strategy with its simple structure.

Słowa kluczowe

EN

electric drive system

• Wydawca: De Gruyter
• Czasopismo: Power Electronics and Drives
• Rocznik: 2023
• Tom: Vol. 8 (43)
• Strony: 325--334
• Opis fizyczny: Bibliogr. 16 poz., rys.

Twórcy

autor

Zerdali Emrah

• Ege University, Department of Electrical and Electronics Engineering, 35040 Izmir, Türkiye

• https://orcid.org/0000-0003-1755-0327

autor

Gurel Aycan

• Niğde Ömer Halisdemir University, Department of Electrical and Electronics Engineering, 51200 Niğde, Türkiye

• https://orcid.org/0000-0003-0386-9193

Bibliografia

• Arshad, M.H., Abido, M.A., Salem, A., Elsayed, A.H., 2019. Weighting Factors Optimization of Model Predictive Torque Control of Induction Motor Using NSGA-II With TOPSIS Decision Making. IEEE Access 7, 177595-177606. https://doi.org/10.1109/ ACCESS.2019.2958415
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Uwagi

Special Section - Artificial Intelligent Based Designs and Applications for the Control of Electrical Drives

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).