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Utilizing global-best harmony search to train a PID-like ANFIS controller


Citation

Lutfy, Omar F. and Mohd Noor, Samsul Bahari and Marhaban, Mohammad Hamiruce and Abbas, Kassim A. (2010) Utilizing global-best harmony search to train a PID-like ANFIS controller. Australian Journal of Basic and Applied Sciences, 4 (12). pp. 6319-6330. ISSN 1991-8178

Abstract

This paper presents a PID-like adaptive neuro-fuzzy inference system (ANFIS) controller that can be trained by the global-best harmony search (GHS) technique to control nonlinear systems. Instead of the hybrid learning methods that are widely used in the literature to train the ANFIS structure, the GHS technique alone is used to train the ANFIS as a feedback controller, and hence, the necessity for the teaching signal required by other techniques has been eliminated. Moreover, the input and output scaling factors for this controller are also determined by the GHS. To show the effectiveness of this controller and its learning method, two nonlinear plants, including the continuous stirred tank reactor (CSTR), were used to test its performance in terms of generalization ability and reference tracking. In addition, this controller robustness to output disturbances has been also tested and the results clearly indicate the remarkable performance of this controller.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
Publisher: American-Eurasian Network for Scientific Information
Keywords: ANFIS; CSTR; Global-best harmony search; Harmony search
Depositing User: Nabilah Mustapa
Date Deposited: 27 Nov 2015 09:04
Last Modified: 27 Nov 2015 09:04
URI: http://psasir.upm.edu.my/id/eprint/22929
Statistic Details: View Download Statistic

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