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Published in: Neural Computing and Applications 7/2016

01-10-2016 | Original Article

Optimal PID-type fuzzy logic controller for a multi-input multi-output active magnetic bearing system

Authors: Amin Noshadi, Juan Shi, Wee Sit Lee, Peng Shi, Akhtar Kalam

Published in: Neural Computing and Applications | Issue 7/2016

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Abstract

The performance of the fuzzy controllers depends highly on the proper selection of some design parameters which is usually tuned iteratively via a trial and error process based primarily on engineering intuition. With the recent developments in the area of global optimization, it has been made possible to obtain the optimal values of the design parameters systematically. Nevertheless, it is well known that unless a priori knowledge is available about the optimization search-domain, most of the available time-domain objective functions may result in undesirable solutions. It is consequently important to provide guidelines on how these parameters affect the closed-loop behavior. As a result, some alternative objective functions are presented for the time-domain optimization of the fuzzy controllers, and the design parameters of a PID-type fuzzy controller are tuned by using the proposed time-domain objective functions. Finally, the real-time application of the optimal PID-type fuzzy controller is investigated on the robust stabilization of a laboratory active magnetic bearing system. The experimental results show that the designed PID-type fuzzy controllers provide much superior performances than the linear on-board controllers while retaining lower profiles of control signals.

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Metadata
Title
Optimal PID-type fuzzy logic controller for a multi-input multi-output active magnetic bearing system
Authors
Amin Noshadi
Juan Shi
Wee Sit Lee
Peng Shi
Akhtar Kalam
Publication date
01-10-2016
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 7/2016
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-015-1996-7

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