[Books-Free DownLoad] -FUZZY LOGIC CONTROL for Mechatronics & Robotics, Part 1

[Books-Free DownLoad] -FUZZY LOGIC CONTROL for Mechatronics & Robotics, Part 1

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1. 

Fuzzy Logic: Algorithms, Techniques And Implementations Ed.

Book Description:

The purpose of this book is to introduce Hybrid Algorithms, Techniques, and Implementations of Fuzzy Logic. The book consists of thirteen chapters highlighting models and principles of fuzzy logic and issues on its techniques and implementations. The intended readers of this book are engineers, researchers, and graduate students interested in fuzzy logic systems

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2. 

Fuzzy Differential Equations In Various Approaches

Book Description:

This book may be used as reference for graduate students interested in fuzzy differential equations and researchers working in fuzzy sets and systems, dynamical systems, uncertainty analysis, and applications of uncertain dynamical systems. Beginning with a historical overview and introduction to fundamental notions of fuzzy sets, including different possibilities of fuzzy differentiation and metric spaces, this book moves on to an overview of fuzzy calculus thorough exposition and comparison of different approaches. Innovative theories of fuzzy calculus and fuzzy differential equations using fuzzy bunches of functions are introduced and explored. Launching with a brief review of essential theories, this book investigates both well-known and novel approaches in this field; such as the Hukuhara differentiability and its generalizations as well as differential inclusions and Zadeh’s extension. Through a unique analysis, results of all these theories are examined and compared.

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3. 

Fuzzy Controllers: Recent Advances In Theory And Applications

Book Description:

This book will provide you a very clear picture of current status of fuzzy control research. This book is intended for researchers, engineers, and postgraduate students specializing in fuzzy systems, control engineering, and robotics.

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4. 

Fuzzy Inference System - Theory and Applications

Book Description:

This book is an attempt to accumulate the researches on diverse inter disciplinary field of engineering and management using Fuzzy Inference System (FIS).

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5. 

Fuzzy Logic Applications In Engineering Science

Book Description:

Fuzzy logic is a relatively new concept in science applications. Hitherto, fuzzy logic has been a conceptual process applied in the field of risk management. Its potential applicability is much wider than that, however, and its particular suitability for expanding our understanding of processes and information in science and engineering in our post-modern world is only just beginning to be appreciated. Written as a companion text to the author’s earlier volume 'An Introduction to Fuzzy Logic Applications', the book is aimed at professional engineers and students and those with an interest in exploring the potential of fuzzy logic as an information processing kit with a wide variety of practical applications in the field of engineering science and develops themes and topics introduced in the author’s earlier text.

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6. 

Mobile Intelligent Autonomous Systems

Book Description:

Going beyond the traditional field of robotics to include other mobile vehicles, Mobile Intelligent Autonomous Systems describes important theoretical concepts, techniques, approaches, and applications that can be used to build truly mobile intelligent autonomous systems (MIAS). It offers a comprehensive treatment of robotics and MIAS, as well as related disciplines, helping readers understand the subject from a system-theoretic and practical point of view. Organized into three sections, the book progresses from conceptual foundations to MIAS and robotics systems and then examines allied technologies. With an emphasis on recent research and developments, experts from various fields cover key aspects of this rapidly emerging area, including:

• Path and motion planning
• Obstacle avoidance in a dynamic environment
• Direct biological-brain control of a mobile robot
• Sensor and image data fusion
• Autonomous decision making and behavior modeling in robots
• Hydro-MiNa robot technology
• Adaptive algorithms for smart antennas
• Control methods for autonomous micro-air vehicles
• Neuro-fuzzy fault-tolerant auto-landing for aircraft
• H-infinity filter based estimation for simultaneous localization and mapping

Where relevant, concepts and theories are illustrated with block/flow diagrams and numerical simulations in MATLAB®. An integrated exploration of the theory and practice of MIAS and robotics, this is a valuable reference and recipe book for research and industry.

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7. 

Between Mind and Computer: Fuzzy Science and Engineering

Book Description:

The “Fuzzy Explosion” emanating from Japan has compelled more people than ever to ponder the meaning and potential of fuzzy engineering. Scientists all over are now beginning to harness the power of fuzzy recognition and decision-making — reminescent of the way the human mind works — in computer applications.In this book a blue-ribbon list of contributors discusses the latest developments in topics such as possibility logic programming, truth-valued flow inference, fuzzy neural-logic networks and default knowledge representation. This volume is the first in a series aiming to document advances in fuzzy set theory and its applications.

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8. 

Fuzzy Arbitrary Order System: Fuzzy Fractional Differential Equations and Applications

Book Description:

Presents a systematic treatment of fuzzy fractional differential equations as well as newly developed computational methods to model uncertain physical problems

Complete with comprehensive results and solutions, Fuzzy Arbitrary Order System: Fuzzy Fractional Differential Equations and Applications details newly developed methods of fuzzy computational techniquesneeded to model solve uncertainty. Fuzzy differential equations are solved via various analytical andnumerical methodologies, and this book presents their importance for problem solving, prototypeengineering design, and systems testing in uncertain environments.

In recent years, modeling of differential equations for arbitrary and fractional order systems has been increasing in its applicability, and as such, the authors feature examples from a variety of disciplines to illustrate the practicality and importance of the methods within physics, applied mathematics, engineering, and chemistry, to name a few. The fundamentals of fractional differential equations and the basic preliminaries of fuzzy fractional differential equations are first introduced, followed by numerical solutions, comparisons of various methods, and simulated results. In addition, fuzzy ordinary, partial, linear, and nonlinear fractional differential equations are addressed to solve uncertainty in physical systems. In addition, this book features:

• Basic preliminaries of fuzzy set theory, an introduction of fuzzy arbitrary order differential equations, and various analytical and numerical procedures for solving associated problems

• Coverage on a variety of fuzzy fractional differential equations including structural, diffusion, and chemical problems as well as heat equations and biomathematical applications

• Discussions on how to model physical problems in terms of nonprobabilistic methods and provides systematic coverage of fuzzy fractional differential equations and its applications

• Uncertainties in systems and processes with a fuzzy concept

Fuzzy Arbitrary Order System: Fuzzy Fractional Differential Equations and Applications is an ideal resource for practitioners, researchers, and academicians in applied mathematics, physics, biology, engineering, computer science, and chemistry who need to model uncertain physical phenomena and problems. The book is appropriate for graduate-level courses on fractional differential equations for students majoring in applied mathematics, engineering, physics, and computer science.

Snehashish Chakraverty, PhD, is Professor and Head of the Department of Mathematics at the National Institute of Technology, Rourkela in India. The author of five books and approximately 140 journal articles, his research interests include mathematical modeling, machine intelligence, uncertainty modeling, numerical analysis, and differential equations.

Smita Tapaswini, PhD, is Assistant Professor in the Department of Mathematics at the Kalinga Institute of Industrial Technology University in India and is also Post-Doctoral Fellow at the College of Mathematics and Statistics at Chongqing University in China. Her research interests include fuzzy differential equations, fuzzy fractional differential equations, and numerical analysis.

Diptiranjan Behera, PhD, is Post-Doctoral Fellow at the Institute of Reliability Engineering in the School of Mechatronics Engineering at the University of Electronic Science and Technology of China. His current research interests include interval and fuzzy mathematics, fuzzy finite element methods, and fuzzy structural analysis.

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9. 

New Backpropagation Algorithm with Type-2 Fuzzy Weights for Neural Networks

Book Description:

In this book a neural network learning method with type-2 fuzzy weight adjustment is proposed. The mathematical analysis of the proposed learning method architecture and the adaptation of type-2 fuzzy weights are presented. The proposed method is based on research of recent methods that handle weight adaptation and especially fuzzy weights.The internal operation of the neuron is changed to work with two internal calculations for the activation function to obtain two results as outputs of the proposed method. Simulation results and a comparative study among monolithic neural networks, neural network with type-1 fuzzy weights and neural network with type-2 fuzzy weights are presented to illustrate the advantages of the proposed method.The proposed approach is based on recent methods that handle adaptation of weights using fuzzy logic of type-1 and type-2. The proposed approach is applied to a cases of prediction for the Mackey-Glass (for ô=17) and Dow-Jones time series, and recognition of person with iris biometric measure. In some experiments, noise was applied in different levels to the test data of the Mackey-Glass time series for showing that the type-2 fuzzy backpropagation approach obtains better behavior and tolerance to noise than the other methods.The optimization algorithms that were used are the genetic algorithm and the particle swarm optimization algorithm and the purpose of applying these methods was to find the optimal type-2 fuzzy inference systems for the neural network with type-2 fuzzy weights that permit to obtain the lowest prediction error.

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10. 

Fuzzy Logic in Its 50th Year: New Developments, Directions and Challenges

Book Description:

This book offers a multifaceted perspective on fuzzy set theory, discussing its developments over the last 50 years. It reports on all types of fuzzy sets, from ordinary to hesitant fuzzy sets, with each one explained by its own developers, authoritative scientists well known for their previous works. Highlighting recent theorems and proofs, the book also explores how fuzzy set theory has come to be extensively used in almost all branches of science, including the health sciences, decision science, earth science and the social sciences alike. It presents a wealth of real-world sample applications, from routing problem to robotics, and from agriculture to engineering. By offering a comprehensive, timely and detailed portrait of the field, the book represents an excellent reference guide for researchers, lecturers and postgraduate students pursuing research on new fuzzy set extensions.

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