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A Comparison of DE and SFLA Optimization Algorithms in Tuning Parameters of Fuzzy Logic Controller

by Duc Hoang Nguyen
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 156 - Number 11
Year of Publication: 2016
Authors: Duc Hoang Nguyen
10.5120/ijca2016912557

Duc Hoang Nguyen . A Comparison of DE and SFLA Optimization Algorithms in Tuning Parameters of Fuzzy Logic Controller. International Journal of Computer Applications. 156, 11 ( Dec 2016), 17-22. DOI=10.5120/ijca2016912557

@article{ 10.5120/ijca2016912557,
author = { Duc Hoang Nguyen },
title = { A Comparison of DE and SFLA Optimization Algorithms in Tuning Parameters of Fuzzy Logic Controller },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2016 },
volume = { 156 },
number = { 11 },
month = { Dec },
year = { 2016 },
issn = { 0975-8887 },
pages = { 17-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume156/number11/26753-2016912557/ },
doi = { 10.5120/ijca2016912557 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:02:20.534717+05:30
%A Duc Hoang Nguyen
%T A Comparison of DE and SFLA Optimization Algorithms in Tuning Parameters of Fuzzy Logic Controller
%J International Journal of Computer Applications
%@ 0975-8887
%V 156
%N 11
%P 17-22
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The paper presents using Differential Evolution (DE) and Shuffled Frog Leaping Algorithm (SFLA) to optimally tune parameters of a fuzzy logic controller stabilizing a rotary inverted pendulum system at its upright equilibrium position. Both the DE and SFLA are meta-heuristic search methods. DE belongs to the class of evolutionary algorithms while SFLA is inspired from the memetic evolution of a group of frogs when seeking for food. In this study, the rule base of the Fuzzy Logic Controller (FLC) is brought by expert experience, and the parameters of the controller, i.e. the membership function parameters and scaling gains, are optimally tuned by the DE and SFLA such that a predefined criterion is minimized. Simulation results show that the designed fuzzy controller is able to balance the rotary inverted pendulum system around its equilibrium state. Besides, convergent rate of SFLA is faster than that of DE but DE has ability to find optimal solutions better than SFLA does.

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Index Terms

Computer Science
Information Sciences

Keywords

Optimization DE SFLA Fuzzy Controller

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