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

237 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
EventGenetic and Evolutionary Computation Conference 2007 - London, United Kingdom
Duration: 7 Jul 200711 Jul 2007
http://www.informatik.uni-trier.de/~ley/db/conf/gecco/gecco2007.html

Conference

ConferenceGenetic and Evolutionary Computation Conference 2007
CountryUnited Kingdom
CityLondon
Period07/07/200711/07/2007
Internet address

Cite this

Achiche, S., Wang, W., Fan, Z., Özkil, A. G., Sørensen, T., Wang, J., & Goodman, E. (2007). Genetically Generated Double-Level Fuzzy Controller with a Fuzzy Adjustment Strategy. In Genetic and Evolutionary Computation Conference 2007 (pp. 1880-1887)