Application of GA-fuzzy controller design to automatic generation control

Craig D. Boesack; Tshilidzi Marwala; Fulufhelo V. Nelwamondo

doi:10.1109/IWACI.2010.5585127

Application of GA-fuzzy controller design to automatic generation control

Craig D. Boesack, Tshilidzi Marwala, Fulufhelo V. Nelwamondo

Faculty of Engineering and the Built Environment

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

7 Citations (Scopus)

Abstract

The design of fuzzy logic controllers involves the rationalization of the Fuzzy Inferencing Rules and the appropriate selection of the input and output membership functions. This typically have been achieved by the application of expert knowledge of plant operation and by the appropriate selection of weighting gains. This paper presents the fuzzy logic controller with certain parameters which can be optimized to suite the specific application under control. Traditionally, this has been performed manually by design. However, contained within this study, Genetic Algorithms are applied as a plausible fuzzy logic controller optimizer (Genetic Fuzzy Controller), and is applied to the Automatic Generation Control problem of large interconnected power systems.

Original language	English
Title of host publication	3rd International Workshop on Advanced Computational Intelligence, IWACI 2010
Pages	227-232
Number of pages	6
DOIs	https://doi.org/10.1109/IWACI.2010.5585127
Publication status	Published - 2010
Event	3rd International Workshop on Advanced Computational Intelligence, IWACI 2010 - Suzhou, China Duration: 25 Aug 2010 → 27 Aug 2010

Publication series

Name	3rd International Workshop on Advanced Computational Intelligence, IWACI 2010

Conference

Conference	3rd International Workshop on Advanced Computational Intelligence, IWACI 2010
Country/Territory	China
City	Suzhou
Period	25/08/10 → 27/08/10

ASJC Scopus subject areas

Artificial Intelligence
Computational Theory and Mathematics

Access to Document

10.1109/IWACI.2010.5585127

Cite this

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title = "Application of GA-fuzzy controller design to automatic generation control",

abstract = "The design of fuzzy logic controllers involves the rationalization of the Fuzzy Inferencing Rules and the appropriate selection of the input and output membership functions. This typically have been achieved by the application of expert knowledge of plant operation and by the appropriate selection of weighting gains. This paper presents the fuzzy logic controller with certain parameters which can be optimized to suite the specific application under control. Traditionally, this has been performed manually by design. However, contained within this study, Genetic Algorithms are applied as a plausible fuzzy logic controller optimizer (Genetic Fuzzy Controller), and is applied to the Automatic Generation Control problem of large interconnected power systems.",

author = "Boesack, {Craig D.} and Tshilidzi Marwala and Nelwamondo, {Fulufhelo V.}",

year = "2010",

doi = "10.1109/IWACI.2010.5585127",

language = "English",

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pages = "227--232",

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note = "3rd International Workshop on Advanced Computational Intelligence, IWACI 2010 ; Conference date: 25-08-2010 Through 27-08-2010",

}

Boesack, CD, Marwala, T & Nelwamondo, FV 2010, Application of GA-fuzzy controller design to automatic generation control. in 3rd International Workshop on Advanced Computational Intelligence, IWACI 2010., 5585127, 3rd International Workshop on Advanced Computational Intelligence, IWACI 2010, pp. 227-232, 3rd International Workshop on Advanced Computational Intelligence, IWACI 2010, Suzhou, China, 25/08/10. https://doi.org/10.1109/IWACI.2010.5585127

Application of GA-fuzzy controller design to automatic generation control. / Boesack, Craig D.; Marwala, Tshilidzi; Nelwamondo, Fulufhelo V.
3rd International Workshop on Advanced Computational Intelligence, IWACI 2010. 2010. p. 227-232 5585127 (3rd International Workshop on Advanced Computational Intelligence, IWACI 2010).

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

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N2 - The design of fuzzy logic controllers involves the rationalization of the Fuzzy Inferencing Rules and the appropriate selection of the input and output membership functions. This typically have been achieved by the application of expert knowledge of plant operation and by the appropriate selection of weighting gains. This paper presents the fuzzy logic controller with certain parameters which can be optimized to suite the specific application under control. Traditionally, this has been performed manually by design. However, contained within this study, Genetic Algorithms are applied as a plausible fuzzy logic controller optimizer (Genetic Fuzzy Controller), and is applied to the Automatic Generation Control problem of large interconnected power systems.

AB - The design of fuzzy logic controllers involves the rationalization of the Fuzzy Inferencing Rules and the appropriate selection of the input and output membership functions. This typically have been achieved by the application of expert knowledge of plant operation and by the appropriate selection of weighting gains. This paper presents the fuzzy logic controller with certain parameters which can be optimized to suite the specific application under control. Traditionally, this has been performed manually by design. However, contained within this study, Genetic Algorithms are applied as a plausible fuzzy logic controller optimizer (Genetic Fuzzy Controller), and is applied to the Automatic Generation Control problem of large interconnected power systems.

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T3 - 3rd International Workshop on Advanced Computational Intelligence, IWACI 2010

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BT - 3rd International Workshop on Advanced Computational Intelligence, IWACI 2010

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ER -

Application of GA-fuzzy controller design to automatic generation control

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