Optimisation of Model Predictive Torque Control Strategy with Standard and Multi-Objective Genetic Algorithms
Küçük Resim Yok
Tarih
2023
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Sciendo
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
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 strate-gy. 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.
Açıklama
Anahtar Kelimeler
Electric Drive System, Induction Motor, Model Predictive Control, Optimisation, Genetic Algorithm
Kaynak
Power Electronics and Drives
WoS Q Değeri
N/A
Scopus Q Değeri
Cilt
8
Sayı
1
