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

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

United Technologies Research Center
Michigan State University

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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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 language	English
Title of host publication	Genetic and Evolutionary Computation Conference 2007
Number of pages	8
Publication date	2007
Pages	1880-1887
Publication status	Published - 2007
Event	2007 Genetic and Evolutionary Computation Conference - London, United Kingdom Duration: 7 Jul 2007 → 11 Jul 2007 http://www.informatik.uni-trier.de/~ley/db/conf/gecco/gecco2007.html

Conference

Conference	2007 Genetic and Evolutionary Computation Conference
Country/Territory	United Kingdom
City	London
Period	07/07/2007 → 11/07/2007
Internet address	http://www.informatik.uni-trier.de/~ley/db/conf/gecco/gecco2007.html

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@inproceedings{db48d1476e5f44f99af2241a318ce6d4,

title = "Genetically Generated Double-Level Fuzzy Controller with a Fuzzy Adjustment Strategy",

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.",

author = "Sofiane Achiche and Wei Wang and Zhun Fan and {\"O}zkil, \{Ali G{\"u}rcan\} and Torben S{\o}rensen and Jiachuan Wang and Erik Goodman",

year = "2007",

language = "English",

pages = "1880--1887",

booktitle = "Genetic and Evolutionary Computation Conference 2007",

note = "2007 Genetic and Evolutionary Computation Conference , GECCO 2007 ; Conference date: 07-07-2007 Through 11-07-2007",

url = "http://www.informatik.uni-trier.de/\textasciitilde{}ley/db/conf/gecco/gecco2007.html",

}

TY - GEN

T1 - Genetically Generated Double-Level Fuzzy Controller with a Fuzzy Adjustment Strategy

AU - Achiche, Sofiane

AU - Wang, Wei

AU - Fan, Zhun

AU - Özkil, Ali Gürcan

AU - Sørensen, Torben

AU - Wang, Jiachuan

AU - Goodman, Erik

PY - 2007

Y1 - 2007

N2 - 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.

AB - 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.

M3 - Article in proceedings

SP - 1880

EP - 1887

BT - Genetic and Evolutionary Computation Conference 2007

T2 - 2007 Genetic and Evolutionary Computation Conference

Y2 - 7 July 2007 through 11 July 2007

ER -

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

Abstract

Conference

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