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Tracking Performance Of Maglev System Using Type-2 Fuzzy Logic Control

of type-2 fuzzy logic systems. Uncertainty is an inherent part of intelligent systems used in real world applications. Conventional controllers;

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Uncertain Rule-Based Fuzzy Logic Systems

uncertainties are present in a problem, much better performance is obtained by using a type-2 fuzzy logic system than by using a type-1 fuzzy logic;

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Differential Evolution Algorithm with Type-2 Fuzzy Logic for Dynamic Parameter Adaptation with Application to Intelligent Control

inverted pendulum controllers are considered. For these 4 problems, experimentation was carried out using a Type-1 fuzzy system and an Interval;

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Fuzzy Control Systems

This book reviews fuzzy control systems. Chapter One presents a new class of fuzzy logic systems named type-2 fuzzy logic systems (T2FLS;

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Vision-Based Mobile Robot Control and Path Planning Algorithms in Obstacle Environments Using Type-2 Fuzzy Logic

the first time in conducted experiments. Four different control algorithms, Type-1 fuzzy logic, Type-2 Fuzzy Logic, Decision Tree Control, and;

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Design of GA-Fuzzy Controller for Magnetic Levitation Using FPGA

problems, is the use of fuzzy logic control. This book will discuss the Magnetic Levitation (Maglev) models as an example of nonlinear systems. It;

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Optimization of Type 2 Fuzzy Controllers Using the Bee Colony Algorithm

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;

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Edge Detection Methods Based on Generalized Type 2 Fuzzy Logic

goal of using generalized type-2 fuzzy logic in edge detec-tion applications is to provide them with the ability to handle uncertainty;

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Extension of the Fuzzy Sugeno Integral Based on Generalized Type-2 Fuzzy Logic

This book presents an extension of the aggregation operator of the generalized interval type-2 Sugeno integral using generalized type-2;

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Introduction To Type-2 Fuzzy Logic Control

Written by world-class leaders in type-2 fuzzy logic control, this book offers a self-contained reference for both researchers and students;

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Fuzzy Logic Speed Controllers Using FPGA Technique

In this Book, a modern FPGA card (Spartan-3A, Xilinx Company) is used to realized a novel Fuzzy- PID control strategy on a complex system;

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Hierarchical Type-2 Fuzzy Aggregation of Fuzzy Controllers

This book focuses on the fields of fuzzy logic, granular computing and also considering the control area. These areas can work together;

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Soft Computing with NeuroFuzzy Systems

collaborative applications in robotics using LabVIEW; and adaptive fuzzy sliding mode control scheme for robotic systems.;

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Type 2 Fuzzy Neural Networks and Their Applications

This book deals with the theory, design principles, and application of hybrid intelligent systems using type-2 fuzzy sets in combination;

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Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms

their performance. The book also presents new and advanced models and algorithms of type-2 fuzzy logic and intuitionistic fuzzy systems, which;

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Applications of Fuzzy Logic Time Control in Industrial Automation

enhancement and consider the cost management of the product. A new approach of Fuzzy Logic Time Control Discrete Event System DEV provides an;

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Hybrid Intelligent Systems in Control, Pattern Recognition and Medicine

type-2 fuzzy logic and their applications; the second explores new concepts and algorithms in neural networks and fuzzy logic applied to;

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Hybrid Intelligent Systems in Control, Pattern Recognition and Medicine

type-2 fuzzy logic and their applications; the second explores new concepts and algorithms in neural networks and fuzzy logic applied to;

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Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms

. 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;

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Multi-Sensor Data Fusion With MATLAB

strategies and algorithms for DF and tracking performance, the book evaluates DF algorithms, software, and systems. It next covers fuzzy logic, fuzzy;

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Recent Advances of Hybrid Intelligent Systems Based on Soft Computing

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;

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Power Quality Issues: Current Harmonics

results Proposes SHAF control strategies using type 1 and type 2 fuzzy logic controllers (FLCs) with different fuzzy membership functions;

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Power Quality Issues: Current Harmonics

SHAF control strategies using type 1 and type 2 fuzzy logic controllers (FLCs) with different fuzzy membership functions (MFs), analyzing their;

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Fuzzy Control Systems

solutions. Control systems based on the fuzzy logic theory can become more functional and flexible in comparison with conventional control systems;

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Model Based Fuzzy Control

Model Based Fuzzy Control uses a given conventional or fuzzy open loop model of the plant under control to derive the set of fuzzy rules;

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Neuro-Fuzzy Equalizers for Mobile Cellular Channels

simulation of wireless channel equalizers using the adaptive-network-based fuzzy inference system (ANFIS). The book highlights a study of currently;

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Neuro-Fuzzy Equalizers for Mobile Cellular Channels

simulation of wireless channel equalizers using the adaptive-network-based fuzzy inference system (ANFIS). The book highlights a study of currently;

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