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Multi-Population Genetic Algorithms for Tuning Fuzzy Logic Controller

Munther N. Al-Tikriti*, Rokaia Sh. Al-Joubori**

* Professor of Control Engineering Faculty of Engineering, Philodeiphlo University

** Assistont Lecturer in System Progromming ond Advonced Digifol Systems, Department of Computer ond Software Engineering College of Engineering Ai-Mustonsiryoh Universify

Periodicity:October - December'2007
DOI : https://doi.org/10.26634/jse.2.2.593

Abstract

Reducing the time required to reach acceptable solutions was the main goal behind parallel implementation of genetic algorithms (Gas). Starting at this point the presented paper introduces a parallel implementation of multi-population genetic algorithms to tune the fuzzy membership functions of a fuzzy logic controller (FLC) with the goal to improve its performance. The genetically tuned controller is implemented for both linear and nonlinear control systems.

Keywords

How to Cite this Article?

Munther N. Al-Tikriti and Rokaia Sh. Al-Joubori (2007). Multi-Population Genetic Algorithms for Tuning Fuzzy Logic Controller. i-manager’s Journal on Software Engineering, 2(2), 56-63. https://doi.org/10.26634/jse.2.2.593

References

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Multi-Population Genetic Algorithms for Tuning Fuzzy Logic Controller

Abstract

Keywords

How to Cite this Article?

References

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