A stochastic multi-parameters divergence method for online auto-tuning of fractional order PID controllers

YEROĞLU, CELALEDDİN; ATEŞ, ABDULLAH

doi:10.1016/j.jfranklin.2013.12.006

A stochastic multi-parameters divergence method for online auto-tuning of fractional order PID controllers

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, cilt.351, sa.5, ss.2411-2429, 2014 (SCI-Expanded)

Yayın Türü: Makale / Tam Makale
Cilt numarası: 351 Sayı: 5
Basım Tarihi: 2014
Doi Numarası: 10.1016/j.jfranklin.2013.12.006
Dergi Adı: JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
Sayfa Sayıları: ss.2411-2429
İnönü Üniversitesi Adresli: Evet

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.