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

被引:0
|
作者
Amin Noshadi
Juan Shi
Wee Sit Lee
Peng Shi
Akhtar Kalam
机构
[1] Victoria University,College of Engineering and Science
[2] The University of Adelaide,School of Electrical and Electronic Engineering
来源
关键词
PID-type fuzzy logic controller; Active magnetic bearing system; Genetic algorithm; Particle swarm optimization; Grey wolf optimization; Imperialist competitive algorithm;
D O I
暂无
中图分类号
学科分类号
摘要
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.
引用
收藏
页码:2031 / 2046
页数:15
相关论文
共 50 条
  • [1] Optimal PID-type fuzzy logic controller for a multi-input multi-output active magnetic bearing system
    Noshadi, Amin
    Shi, Juan
    Lee, Wee Sit
    Shi, Peng
    Kalam, Akhtar
    NEURAL COMPUTING & APPLICATIONS, 2016, 27 (07): : 2031 - 2046
  • [2] PID-type Fuzzy Logic Controller for Active Magnetic Bearing System
    Noshadi, Amin
    Shi, Juan
    Lee, WeeSit
    Kalam, Akhtar
    IECON 2014 - 40TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, 2014, : 241 - 247
  • [3] Design and Implementation of an Integrated Fuzzy Logic Controller for a Multi-input Multi-output System
    Patil, S. S.
    Bhaskar, P.
    Sudheer, L. Shrimanth
    DEFENCE SCIENCE JOURNAL, 2011, 61 (03) : 219 - 227
  • [4] Multi-input multi-output fuzzy logic controller for utility electric vehicle
    Gasbaoui, Brahim
    Abdelkader, Chaker
    Adellah, Laoufi
    ARCHIVES OF ELECTRICAL ENGINEERING, 2011, 60 (03) : 239 - 256
  • [5] Design of a multi-layer fuzzy logic controller for multi-input multi-output systems
    Tu, KY
    Lee, TT
    Wang, WJ
    FUZZY SETS AND SYSTEMS, 2000, 111 (02) : 199 - 214
  • [6] Hierarchical Fuzzy Logic for Multi-Input Multi-Output Systems
    Kamthan, Shashank
    Singh, Harpreet
    IEEE ACCESS, 2020, 8 : 206966 - 206981
  • [7] Evolutionary design of PID controller for twin rotor multi-input multi-output system
    Wang, WY
    Lee, TT
    Huang, HC
    PROCEEDINGS OF THE 4TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-4, 2002, : 913 - 917
  • [8] System Identification and Robust Control of Multi-Input Multi-Output Active Magnetic Bearing Systems
    Noshadi, Amin
    Shi, Juan
    Lee, Wee Sit
    Shi, Peng
    Kalam, Akhtar
    IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2016, 24 (04) : 1227 - 1239
  • [9] Optimal single input PID-type fuzzy logic controller
    Lee, Shih-Chih
    Shih, Ching-Long
    JOURNAL OF THE CHINESE INSTITUTE OF ENGINEERS, 2012, 35 (04) : 413 - 420
  • [10] Multi-input multi-output fuzzy logic controller for complex system: Application on two-links manipulator
    Baghli, Fatima Zahra
    El Bakkali, Larbi
    Lakhal, Yassine
    8TH INTERNATIONAL CONFERENCE INTERDISCIPLINARITY IN ENGINEERING, INTER-ENG 2014, 2015, 19 : 607 - 614