IDEAS home Printed from https://ideas.repec.org/a/wsi/ijitdm/v14y2015i05ns0219622015500273.html
   My bibliography  Save this article

Optimization of Fuzzy Logic Controllers with Rule Base Size Reduction using Genetic Algorithms

Author

Listed:
  • Pintu Chandra Shill

    (Department of Computer Science and Engineering, Khulna University of Engineering & Technology, Khulna 9203, Bangladesh)

  • M. A. H. Akhand

    (Department of Computer Science and Engineering, Khulna University of Engineering & Technology, Khulna 9203, Bangladesh)

  • MD. Asaduzzaman

    (Department of System Design Engineering, University of Fukui, 3-9-1 Bunkyo, Fukui-910-8507, Japan)

  • Kazuyuki Murase

    (Department of System Design Engineering, University of Fukui, 3-9-1 Bunkyo, Fukui-910-8507, Japan)

Abstract

In this paper, we present the automatic design methods with rule base size reduction for fuzzy logic controllers (FLCs) through real and binary coded coupled genetic algorithms (GAs). The adaptive schema is divided into two phases: the first phase is concerned with optimizing the FLCs membership functions and second phase called rule learning and reducing phase which automatically generates the fuzzy rules as well as determines the minimum number of rules required for building the fuzzy models. In the second phase, the redundant rules are removed by setting their all consequent weight factor to zero and merging the conflicting rules during the learning process. The first and second phases are carried out by the real and binary coded coupled GAs, respectively. Optimizing the MFs with learning and reducing rule base concurrently represents a way to maximize the performance of a FLC. The control algorithm is successfully tested for intelligent control of two degrees of freedom inverted pendulum. Finally, the simulation studies exhibits the better or competitive performance of the proposed method when compared with the existing methods.

Suggested Citation

  • Pintu Chandra Shill & M. A. H. Akhand & MD. Asaduzzaman & Kazuyuki Murase, 2015. "Optimization of Fuzzy Logic Controllers with Rule Base Size Reduction using Genetic Algorithms," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 14(05), pages 1063-1092.
    • Handle: RePEc:wsi:ijitdm:v:14:y:2015:i:05:n:s0219622015500273
    DOI: 10.1142/S0219622015500273
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219622015500273
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0219622015500273?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wsi:ijitdm:v:14:y:2015:i:05:n:s0219622015500273. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijitdm/ijitdm.shtml .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.