A stochastic multi-parameters divergence method for online auto-tuning of fractional order PID controllers
Küçük Resim Yok
Tarih
2014
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Pergamon-Elsevier Science Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This paper presents a stochastic multi-parameters divergence method for online parameter optimization of fractional-order proportional-integral-derivative (PID) controllers. The method is used for auto-tuning without the need for exact mathematical plant model and it is applicable to diverse plant transfer functions. The proposed controller tuning algorithm is capable of adaptively responding to parameter fluctuations and model uncertainties in real systems. Adaptation skill enhances controller performance for real-time applications. Simulations and experimental observations are carried on a prototype helicopter model to confirm the performance improvements obtained by the online auto-tuning of fractional-order PID structure in laboratory conditions. (C) 2013 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Açıklama
Anahtar Kelimeler
Design, Gain, Systems
Kaynak
Journal of The Franklin Institute-Engineering and Applied Mathematics
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
351
Sayı
5
