Genetically Generated Double-Level Fuzzy Controller with a Fuzzy Adjustment Strategy

Sofiane Achiche, Wei Wang, Zhun Fan, Ali Gürcan Özkil, Torben Sørensen, Jiachuan Wang, Erik Goodman

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    293 Downloads (Pure)

    Abstract

    This paper describes the use of a genetic algorithm (GA) in tuning a double-level modular fuzzy logic controller (DLMFLC), which can expand its control working zone to a larger spectrum than a single-level FLC. The first-level FLCs are tuned by a GA so that the input parameters of their membership functions and fuzzy rules are optimized according to their individual working zones. The second-level FLC is then used to adjust contributions of the first-level FLCs to the final output signal of the whole controller, i.e., DLMFLC, so that it can function in a wider spectrum covering all individual working zones of the first-level FLCs. The second-level FLC is again optimized by a GA. An inverted pendulum system (IPS) is used to demonstrate the feasibility of the approach.
    Original languageEnglish
    Title of host publicationGenetic and Evolutionary Computation Conference 2007
    Number of pages8
    Publication date2007
    Pages1880-1887
    Publication statusPublished - 2007
    Event2007 Genetic and Evolutionary Computation Conference - London, United Kingdom
    Duration: 7 Jul 200711 Jul 2007
    http://www.informatik.uni-trier.de/~ley/db/conf/gecco/gecco2007.html

    Conference

    Conference2007 Genetic and Evolutionary Computation Conference
    Country/TerritoryUnited Kingdom
    CityLondon
    Period07/07/200711/07/2007
    Internet address

    Fingerprint

    Dive into the research topics of 'Genetically Generated Double-Level Fuzzy Controller with a Fuzzy Adjustment Strategy'. Together they form a unique fingerprint.

    Cite this