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Differential evolution algorithm wit...

Castillo, Oscar.

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Differential evolution algorithm with type-2 fuzzy logic for dynamic parameter adaptation with application to intelligent control

Record Type:	Electronic resources : Monograph/item
Title/Author:	Differential evolution algorithm with type-2 fuzzy logic for dynamic parameter adaptation with application to intelligent control/ by Oscar Castillo, Patricia Ochoa, Jose Soria.
Author:	Castillo, Oscar.
other author:	Ochoa, Patricia.
Published:	Cham :Springer International Publishing : : 2021.,
Description:	vii, 61 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Fuzzy logic. -
Online resource:	https://doi.org/10.1007/978-3-030-62133-9
ISBN:	9783030621339

Differential evolution algorithm with type-2 fuzzy logic for dynamic parameter adaptation with application to intelligent control
Castillo, Oscar.

Differential evolution algorithm with type-2 fuzzy logic for dynamic parameter adaptation with application to intelligent control[electronic resource] /by Oscar Castillo, Patricia Ochoa, Jose Soria. - Cham :Springer International Publishing :2021. - vii, 61 p. :ill., digital ;24 cm. - SpringerBriefs in applied sciences and technology, Computational intelligence. - SpringerBriefs in applied sciences and technology.Computational intelligence..

This book focuses on the fields of fuzzy logic, bio-inspired algorithm, especially the differential evolution algorithm and also considering the fuzzy control area. The main idea is that these two areas together can help solve various control problems and to find better results. In this book, the authors test the proposed method using five benchmark control problems. First, the water tank, temperature, mobile robot, and inverted pendulum controllers are considered. For these 4 problems, experimentation was carried out using a Type-1 fuzzy system and an Interval Type-2 system. The last control problem was the D.C. motor, for which the experiments were performed with Type-1, Interval Type-2, and Generalized Type-2 fuzzy systems. When we use fuzzy systems combined with the differential evolution algorithm, we can notice that the results obtained in each of the controllers are better and with increasing uncertainty, the results are even better. For this reason, the authors consider in this book the proposed method using fuzzy systems and the differential evolution algorithm to improve the fuzzy controllers' behavior in complex control problems.

ISBN: 9783030621339

Standard No.: 10.1007/978-3-030-62133-9doiSubjects--Topical Terms:

532071
Fuzzy logic.

LC Class. No.: QA9.64 / .C37 2021

Dewey Class. No.: 511.313

Differential evolution algorithm with type-2 fuzzy logic for dynamic parameter adaptation with application to intelligent control
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245 1 0 $a Differential evolution algorithm with type-2 fuzzy logic for dynamic parameter adaptation with application to intelligent control $h [electronic resource] / $c by Oscar Castillo, Patricia Ochoa, Jose Soria.
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300 $a vii, 61 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in applied sciences and technology, Computational intelligence
520 $a This book focuses on the fields of fuzzy logic, bio-inspired algorithm, especially the differential evolution algorithm and also considering the fuzzy control area. The main idea is that these two areas together can help solve various control problems and to find better results. In this book, the authors test the proposed method using five benchmark control problems. First, the water tank, temperature, mobile robot, and inverted pendulum controllers are considered. For these 4 problems, experimentation was carried out using a Type-1 fuzzy system and an Interval Type-2 system. The last control problem was the D.C. motor, for which the experiments were performed with Type-1, Interval Type-2, and Generalized Type-2 fuzzy systems. When we use fuzzy systems combined with the differential evolution algorithm, we can notice that the results obtained in each of the controllers are better and with increasing uncertainty, the results are even better. For this reason, the authors consider in this book the proposed method using fuzzy systems and the differential evolution algorithm to improve the fuzzy controllers' behavior in complex control problems.
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700 1 $a Soria, Jose. $3 3487868
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