Modified Artificial Physics Optimization for Multi-parameter Functions
Küçük Resim Yok
Tarih
2018
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer Int Publ Ag
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This paper combines Artificial Physics and Base Optimization Algorithms to propose a Modified Artificial Physics Optimization for multi-parameter function minimization. Prominent features of Base Optimization lies in using standard arithmetic operators with displacement parameters to reach the optimal solution. Artificial Physics benefit from the success of physicomimetics and shows an evident predominance in search of global optima. This study uses distinctive advantages of two algorithms to propose an efficient optimization for multi-parameter functions. In order to reveal effects of mass function approach of Artificial Physics and cost functions of the optimization process, the proposed method executes various mass-cost function combinations synchronously. The effectiveness of the proposed algorithm is demonstrated on integer-order and fractional-order controller tunings for integer- and fractional-order models. Priority of the proposed optimization method is presented by comparing with known optimization algorithms.
Açıklama
Anahtar Kelimeler
Stochastic optimization, Artificial Physics, Base Optimization, Controller tuning, Fractional calculus
Kaynak
Iranian Journal of Science and Technology-Transactions of Electrical Engineering
WoS Q Değeri
Q4
Scopus Q Değeri
Q2
Cilt
42
Sayı
4
