Overview
- Focuses on the fields of fuzzy logic and metaheuristic algorithms, especially the harmony search algorithm and fuzzy control
- Presents a parameter adaptation solution in the original harmony search algorithm using type-1, interval type-2 and generalized type-2 fuzzy logic
- Highlights general type-2 fuzzy logic in dynamic parameter adaptation for the harmony search algorithm
Part of the book series: SpringerBriefs in Applied Sciences and Technology (BRIEFSAPPLSCIENCES)
Part of the book sub series: SpringerBriefs in Computational Intelligence (BRIEFSINTELL)
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Table of contents (5 chapters)
Keywords
About this book
This book focuses on the fields of fuzzy logic and metaheuristic algorithms, particularly the harmony search algorithm and fuzzy control. There are currently several types of metaheuristics used to solve a range of real-world of problems, and these metaheuristics contain parameters that are usually fixed throughout the iterations. However, a number of techniques are also available that dynamically adjust the parameters of an algorithm, such as probabilistic fuzzy logic.
This book proposes a method of addressing the problem of parameter adaptation in the original harmony search algorithm using type-1, interval type-2 and generalized type-2 fuzzy logic. The authors applied this methodology to the resolution of problems of classical benchmark mathematical functions, CEC 2015, CEC2017 functions and to the optimization of various fuzzy logic control cases, and tested the method using six benchmark control problems – four of the Mamdani type: the problem of filling a water tank, theproblem of controlling the temperature of a shower, the problem of controlling the trajectory of an autonomous mobile robot and the problem of controlling the speed of an engine; and two of the Sugeno type: the problem of controlling the balance of a bar and ball, and the problem of controlling control the balance of an inverted pendulum. When the interval type-2 fuzzy logic system is used to model the behavior of the systems, the results show better stabilization because the uncertainty analysis is better. As such, the authors conclude that the proposed method, based on fuzzy systems, fuzzy controllers and the harmony search optimization algorithm, improves the behavior of complex control plants.
Reviews
“The material could be of interest to readers looking for enhancements of existing metaheuristics, especially when being applied to challenging optimization problems.” (Witold Pedrycz, zbMATH 1457.90176, 2021)
Authors and Affiliations
Bibliographic Information
Book Title: General Type-2 Fuzzy Logic in Dynamic Parameter Adaptation for the Harmony Search Algorithm
Authors: Fevrier Valdez, Cinthia Peraza, Oscar Castillo
Series Title: SpringerBriefs in Applied Sciences and Technology
DOI: https://doi.org/10.1007/978-3-030-43950-7
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Author(s), under exclusive license to Springer Nature Switzerland AG 2020
Softcover ISBN: 978-3-030-43949-1Published: 28 March 2020
eBook ISBN: 978-3-030-43950-7Published: 27 March 2020
Series ISSN: 2191-530X
Series E-ISSN: 2191-5318
Edition Number: 1
Number of Pages: VII, 83
Number of Illustrations: 15 b/w illustrations, 32 illustrations in colour
Topics: Computational Intelligence, Artificial Intelligence, Control and Systems Theory