Fitness distance balance-based Runge–Kutta algorithm for indirect rotor field-oriented vector control of three-phase induction motor
Yükleniyor...
Dosyalar
Tarih
2023
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer Science and Business Media Deutschland GmbH
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this article, a study has been carried out to further develop the Runge–Kutta (RK) algorithm, which has a current and robust mathematical structure, using the fitness distance balance (FDB) method, and to test it for induction machine control. The RK algorithm was developed to avoid local optimum solutions, speed up convergence, and seek out the best possible solutions globally. Despite offering promising solutions, it is clear that this algorithm has its shortcomings, especially in solving high-dimensional problems like asynchronous motor control. In this study, the FDB method was used to build the guide selection process in the RK algorithm to reach the optimal solution. The developed FDB-based RK algorithm has been tested and verified on the CEC17 benchmark problems for 30-dimensional search spaces. The results of the proposed algorithm have been compared to the performance of the classical RK algorithm, and it shows that the changes in the design of the RK algorithm are successful. The proportional–integral–derivative (PID) parameters employed as a controller in the indirect rotor field-oriented control approach of a three-phase induction motor have then been optimized using the accuracy-proven algorithm. The FDB-RK, RK, genetic algorithm, particle swarm (PSO), differential evolution, artificial bee colony, and weighted average of vectors (INFO) algorithms have been used in this study with three different fitness functions and Wilcoxon and Freidman statistical analyses to find the best values for PID parameters. According to the data, FDB-RK-based PID controller has the best performance among the techniques. © 2023, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.
Açıklama
Anahtar Kelimeler
Fitness distance balance, Indirect field-oriented control, Optimization, PID controller, Runge–Kutta, Controllers, Electric control equipment, Genetic algorithms, Induction motors, Particle swarm optimization (PSO), Proportional control systems, Robust control, Statistical methods, Vector control (Electric machinery), Balance methods, Distance balance, Fitness distance balance, Indirect field oriented control, Optimisations, Performance, Proportional-integral-derivatives controllers, Runge-Kutta algorithms, Runge–kuttum, Three phase induction motor, Three term control systems
Kaynak
Neural Computing and Applications
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
