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On-line evolution of Takagi-Sugeno fuzzy models

Angelov, Plamen and Victor, Jose and Dourado, Antonio and Filev, Dimitar (2004) On-line evolution of Takagi-Sugeno fuzzy models. In: 2nd IFAC Workshop on Advanced Fuzzy/Neural Control, 2004-09-162004-09-17, Oulu, Finland.

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    Abstract

    Evolving Takagi-Sugeno (eTS) fuzzy models and the method for their on-line identification has been recently introduced for both MISO and MIMO case. In this paper, the mechanism for rule-base evolution, one of the central points of the algorithm together with the recursive clustering and modified recursive least squares (RLS) estimation, is studied in detail. Different scenarios are considered for the rule base upgrade and modification. The radius of influence of each fuzzy rule is considered to be a vector instead of a scalar as in the original eTS approach, allowing different areas of the data space to be covered by each input variable. Simulation results using a well-known benchmark (Mackey-Glass chaotic time-series prediction) are presented. Copyright © 2004 IFAC

    Item Type: Conference or Workshop Item (Paper)
    Journal or Publication Title: 2nd IFAC Workshop on Advanced Fuzzy/Neural Control
    Additional Information: "©2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE." "This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder."
    Uncontrolled Keywords: evolving Takagi-Sugeno fuzzy models ; rule-base evolution ; recursive clustering ; RLS algorithm. DCS-publications-id ; inproc-338 ; DCS-publications-credits ; dsp-fa ; DCS-publications-personnel-id ; 82
    Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
    Departments: Faculty of Science and Technology > School of Computing & Communications
    ID Code: 952
    Deposited By: Dr. Plamen Angelov
    Deposited On: 11 Jan 2008 11:25
    Refereed?: Yes
    Published?: Published
    Last Modified: 21 Mar 2014 10:28
    Identification Number:
    URI: http://eprints.lancs.ac.uk/id/eprint/952

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