Optimization Of Type 2 Fuzzy Controllers Using The Bee Colony Algorithm
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Author |
: Leticia Amador |
Publisher |
: Springer |
Total Pages |
: 77 |
Release |
: 2017-04-27 |
ISBN-10 |
: 9783319542959 |
ISBN-13 |
: 3319542958 |
Rating |
: 4/5 (59 Downloads) |
Synopsis Optimization of Type-2 Fuzzy Controllers Using the Bee Colony Algorithm by : Leticia Amador
This book focuses on the fields of fuzzy logic, bio-inspired algorithm; especially bee colony optimization algorithm and also considering the fuzzy control area. The main idea is that this areas together can to solve various control problems and to find better results. In this book we test the proposed method using two benchmark problems; the problem for filling a water tank and the problem for controlling the trajectory in an autonomous mobile robot. When Interval Type-2 Fuzzy Logic System is implemented to model the behavior of systems, the results show a better stabilization, because the analysis of uncertainty is better. For this reason we consider in this book the proposed method using fuzzy systems, fuzzy controllers, and bee colony optimization algorithm improve the behavior of the complex control problems.
Author |
: Oscar Castillo |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 187 |
Release |
: 2011-10-18 |
ISBN-10 |
: 9783642246623 |
ISBN-13 |
: 3642246621 |
Rating |
: 4/5 (23 Downloads) |
Synopsis Type-2 Fuzzy Logic in Intelligent Control Applications by : Oscar Castillo
We describe in this book, hybrid intelligent systems based mainly on type-2 fuzzy logic for intelligent control. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, and bio-inspired optimization algorithms, which can be used to produce powerful automatic control systems. The book is organized in three main parts, which contain a group of chapters around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which can be the basis for achieving intelligent control with interval type-2 fuzzy logic. The second part of the book is comprised of chapters with the main theme of evolutionary optimization of type-2 fuzzy systems in intelligent control with the aim of designing optimal type-2 fuzzy controllers for complex control problems in diverse areas of application, including mobile robotics, aircraft dynamics systems and hardware implementations. The third part of the book is formed with chapters dealing with the theme of bio-inspired optimization of type-2 fuzzy systems in intelligent control, which includes the application of particle swarm intelligence and ant colony optimization algorithms for obtaining optimal type-2 fuzzy controllers.
Author |
: Oscar Castillo |
Publisher |
: Springer Nature |
Total Pages |
: 792 |
Release |
: 2020-02-27 |
ISBN-10 |
: 9783030354459 |
ISBN-13 |
: 3030354458 |
Rating |
: 4/5 (59 Downloads) |
Synopsis Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications by : Oscar Castillo
This book describes the latest advances in fuzzy logic, neural networks, and optimization algorithms, as well as their hybrid intelligent combinations, and their applications in the areas such as intelligent control, robotics, pattern recognition, medical diagnosis, time series prediction, and optimization. The topic is highly relevant as most current intelligent systems and devices use some form of intelligent feature to enhance their performance. The book also presents new and advanced models and algorithms of type-2 fuzzy logic and intuitionistic fuzzy systems, which are of great interest to researchers in these areas. Further, it proposes novel, nature-inspired optimization algorithms and innovative neural models. Featuring contributions on theoretical aspects as well as applications, the book appeals to a wide audience.
Author |
: Fevrier Valdez |
Publisher |
: Springer Nature |
Total Pages |
: 86 |
Release |
: 2020-03-27 |
ISBN-10 |
: 9783030439507 |
ISBN-13 |
: 303043950X |
Rating |
: 4/5 (07 Downloads) |
Synopsis General Type-2 Fuzzy Logic in Dynamic Parameter Adaptation for the Harmony Search Algorithm by : Fevrier Valdez
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, the problem 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.
Author |
: Allawi Ziyad |
Publisher |
: LAP Lambert Academic Publishing |
Total Pages |
: 136 |
Release |
: 2015-06-11 |
ISBN-10 |
: 3659741574 |
ISBN-13 |
: 9783659741579 |
Rating |
: 4/5 (74 Downloads) |
Synopsis Optimal Fuzzy Controllers for Multi Mobile Robot Navigation by : Allawi Ziyad
In this book, a new optimization technique for Interval Type-2 Fuzzy Logic Controller is introduced which is called "Optimal Defuzzification." This method uses an optimization algorithm instead of the Defuzzification stage to choose the best value inside the Type-1 Fuzzy interval set according to an objective function rather than averaging the borders of that set. The optimization algorithms used in this method are the Particle Swarm Optimizatin (PSO) presented by (Kennedy and Eberhart, 1998) and the Artificial Bee Colony (ABC) presented by (Karabo a, 2005). This optimized fuzzy controller was used to control a group of nonholonomic differential-drive mobile robots in different completely unknown 2-D environments with obstacles. A dynamic mathematical model was used to simulate the robots along with a collision avoidance technique between the moving agents through Velocity Obstacle Algorithm (VO) presented by (Fiorini and Shiller, 1993). Results show that using the Defuzzification-optimized fuzzy controller helps in choosing the collision-free path for every mobile robot to reach its target and avoid colliding with other robots than using the ordinary defuzzified fuzzy controller."
Author |
: Oscar Castillo |
Publisher |
: Springer Nature |
Total Pages |
: 471 |
Release |
: 2022-09-30 |
ISBN-10 |
: 9783031082665 |
ISBN-13 |
: 3031082664 |
Rating |
: 4/5 (65 Downloads) |
Synopsis New Perspectives on Hybrid Intelligent System Design based on Fuzzy Logic, Neural Networks and Metaheuristics by : Oscar Castillo
In this book, recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, are presented. In addition, the above-mentioned methods are applied to areas such as, intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book contains a collection of papers focused on hybrid intelligent systems based on soft computing techniques. There are some papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications. There also some papers that offer theoretical concepts and applications of meta-heuristics in different areas. Another group of papers describe diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical problems. There are also some papers that present theory and practice of neural networks in different areas of application. In addition, there are papers that present theory and practice of optimization and evolutionary algorithms in different areas of application. Finally, there are some papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition and classification problems.
Author |
: Oscar Castillo |
Publisher |
: Springer Nature |
Total Pages |
: 254 |
Release |
: 2023-05-23 |
ISBN-10 |
: 9789811981944 |
ISBN-13 |
: 9811981949 |
Rating |
: 4/5 (44 Downloads) |
Synopsis Applied Mathematics and Computational Intelligence by : Oscar Castillo
This book contains select papers presented at the International Conference on Applied Mathematics and Computational Intelligence (ICAMCI-2020), held at the National Institute of Technology Agartala, Tripura, India, from 19–20 March 2020. It discusses the most recent breakthroughs in intelligent techniques such as fuzzy logic, neural networks, optimization algorithms, and their application in the development of intelligent information systems by using applied mathematics. The book also explains how these systems will be used in domains such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction, and complicated problems in optimization. The book publishes new developments and advances in various areas of type-3 fuzzy, intuitionistic fuzzy, computational mathematics, block chain, creak analysis, supply chain, soft computing, fuzzy systems, hybrid intelligent systems, thermos-elasticity, etc. The book is targeted to researchers, scientists, professors, and students of mathematics, computer science, applied science and engineering, interested in the theory and applications of intelligent systems in real-world applications. It provides young researchers and students with new directions for their future study by exchanging fresh thoughts and finding new problems.
Author |
: Said Melliani |
Publisher |
: Springer |
Total Pages |
: 320 |
Release |
: 2018-10-09 |
ISBN-10 |
: 9783030021559 |
ISBN-13 |
: 3030021556 |
Rating |
: 4/5 (59 Downloads) |
Synopsis Recent Advances in Intuitionistic Fuzzy Logic Systems by : Said Melliani
This book aims at providing an overview of state-of-the-art in both the theory and methods of intuitionistic fuzzy logic, partial differential equations and numerical methods in informatics. It covers topics such as fuzzy intuitionistic Hilbert spaces, intuitionistic fuzzy differential equations, fuzzy intuitionistic metric spaces, and numerical methods for differential equations. It reports on applications such as fuzzy real time scheduling, intelligent control, diagnostics and time series prediction. Chapters were carefully selected among contributions presented at the second edition of the International Conference on Intuitionistic Fuzzy Sets and Mathematical Science, ICIFSMAS, held on April 11-13, 2018, at Al Akhawayn University of Ifrane, in Morocco.
Author |
: Grigori Sidorov |
Publisher |
: Springer |
Total Pages |
: 591 |
Release |
: 2015-11-19 |
ISBN-10 |
: 9783319270609 |
ISBN-13 |
: 3319270605 |
Rating |
: 4/5 (09 Downloads) |
Synopsis Advances in Artificial Intelligence and Soft Computing by : Grigori Sidorov
The two volume set LNAI 9413 + LNAI 9414 constitutes the proceedings of the 14th Mexican International Conference on Artificial Intelligence, MICAI 2015, held in Cuernavaca, Morelos, Mexico, in October 2015. The total of 98 papers presented in these proceedings was carefully reviewed and selected from 297 submissions. They were organized in topical sections named: natural language processing; logic and multi-agent systems; bioinspired algorithms; neural networks; evolutionary algorithms; fuzzy logic; machine learning and data mining; natural language processing applications; educational applications; biomedical applications; image processing and computer vision; search and optimization; forecasting; and intelligent applications.
Author |
: Oscar Castillo |
Publisher |
: Springer Nature |
Total Pages |
: 354 |
Release |
: 2019-11-23 |
ISBN-10 |
: 9783030341350 |
ISBN-13 |
: 3030341356 |
Rating |
: 4/5 (50 Downloads) |
Synopsis Hybrid Intelligent Systems in Control, Pattern Recognition and Medicine by : Oscar Castillo
This book describes the latest advances in fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, and their applications in areas such as: intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction, and optimization of complex problems. The book is divided into five main parts. The first part proposes new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications; the second explores new concepts and algorithms in neural networks and fuzzy logic applied to recognition. The third part examines the theory and practice of meta-heuristics in various areas of application, while the fourth highlights diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical contexts. Finally, the fifth part focuses on applications of fuzzy logic, neural networks and meta-heuristics to robotics problems.