Optimization Of Type-2 Fuzzy Controllers Using The Bee Colony Algorithm

Leticia Amador Oscar Castillo • Optimization of Type-2 Fuzzy Controllers using the Bee Colony Algorithm 123 Leticia Amador Division of Graduate Studies Tijuana Institute of Technology Tijuana, Baja California Mexico Oscar Castillo Division of Graduate Studies Tijuana Institute of Technology Tijuana, Baja California Mexico ISSN 2191-530X ISSN 2191-5318 (electronic) SpringerBriefs in Applied Sciences and Technology ISBN 978-3-319-54294-2 ISBN 978-3-319-54295-9 (eBook) DOI 10.1007/978-3-319-54295-9 Library of Congress Control Number: 2017933057 © The Author(s) 2017 This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Preface This book focuses on the fields of fuzzy logic and bioinspired algorithms, especially the bee colony optimization algorithm, and also considers the fuzzy control area. The main idea is that these areas together can solve various control problems and obtain better results. We test the proposed method using two benchmark problems: filling a water tank and controlling the trajectory in an autonomous mobile robot. When an Interval Type-2 fuzzy logic system is implemented to model the behavior of systems, the results show better stabilization, because the analysis of uncertainty is better. For this reason in this book we consider the proposed method using fuzzy systems, fuzzy controllers, and the bee colony optimization algorithm to improve the behavior of complex control problems. This book is intended to be a reference for scientists and engineers interested in applying fuzzy logic techniques to solve problems in intelligent control. This book can also be used as a reference for graduate courses including: soft computing, swarm intelligence, bioinspired algorithms, intelligent control, and fuzzy control, among others. We consider that this book can also be used to inspire novel ideas for new lines of research, or to continue the lines of research proposed by the authors. In Chap. 1, we begin by offering a brief introduction of the potential use of the optimization strategies in different real-world applications. We describe the use of the bee colony optimization algorithm using Interval Type-2 fuzzy logic systems for aggregation of results in problems of intelligent control of nonlinear plants. We also mention other possible applications of the proposed control approach. We describe in Chap. 2 the basic concepts, notation, and theory of fuzzy logic, and the fuzzy controller. This chapter overviews the background, main definitions, and basic concepts useful for the development of this research work. Chapter 3 describes the two problem statements that are used of complex plants, such as the characteristics and design of the proposed fuzzy logic system and the implementation of the problem with the bee colony optimization. The particular control problems that are used to test the proposed method are explained. A hybrid system composed of two intelligent technologies is used as a new method for global control. This is critical for complex control problems that can be solved by dividing them into several simple controllers. Chapter 4 is devoted to describing the bee colony optimization algorithm and the proposed method in the dynamic adaptation of the parameters using fuzzy sets for control when applied to the particular nonlinear plants that are considered for validating the proposed approach, in particular, the water tank problem and an autonomous mobile robot problem. We offer in Chap. 5 the simulation results with the original bee colony optimization and the proposed method using the interval Type-2 fuzzy logic systems; various performance indices are used to show improvement of the proposed method. In addition, fuzzy and ori