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Fuzzy Control and Filter Design for Uncertain Fuzzy Systems

for an uncertain nonlinear system is to linearize the system about an operating point, and uses linear control theory to design a controller;

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Modeling and Control of Uncertain Nonlinear Systems with Fuzzy Equations and Z-Number

simulations Modeling and Control of Uncertain Nonlinear Systems with Fuzzy Equations and Z-Number is suitable as a textbook for advanced students;

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Introduction to Fuzzy Sets, Fuzzy Logic, and Fuzzy Control Systems

designing and analyzing fuzzy control systems under uncertain and irregular conditions. Mastering its contents gives students a clear understanding;

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Introduction to Fuzzy Sets, Fuzzy Logic, and Fuzzy Control Systems

designing and analyzing fuzzy control systems under uncertain and irregular conditions. Mastering its contents gives students a clear understanding;

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Analysis and Synthesis of Fuzzy Control Systems

lack of tools for systematic stability analysis and controller design. To address this problem, many model-based fuzzy control approaches have;

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Analysis and Synthesis of Fuzzy Control Systems

lack of tools for systematic stability analysis and controller design. To address this problem, many model-based fuzzy control approaches have;

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Control and Filtering of Fuzzy Systems with Switched Parameters

This book presents recent advances in control and filter design for Takagi-Sugeno (T-S) fuzzy systems with switched parameters. Thanks to;

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Control and Filtering of Fuzzy Systems with Switched Parameters

This book presents recent advances in control and filter design for Takagi-Sugeno (T-S) fuzzy systems with switched parameters. Thanks to;

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Fuzzy Control Systems Design And Analysis

stability and design of nonlinear fuzzy control systems. Building on the Takagi-Sugeno fuzzy model, authors Tanaka and Wang address a number;

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Fuzzy Control Systems

concerning the analysis, design, and application of fuzzy control systems. Divided into three parts, the book first devotes itself to the general;

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Uncertain Rule-Based Fuzzy Logic Systems

For courses in Neural Networks and Fuzzy Systems; Fuzzy SystemsControl; Fuzzy Logic.The first book of its kind, this text explains how all;

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Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms

in solving problems, but a definitive theoretical basis does not yet exist for their design. Fusion of Neural Networks, Fuzzy Systems and Genetic;

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Handbook Of Vehicle Suspension Control Systems

control for uncertain vehicle suspension systems via fuzzy control approach; h-infinity fuzzy control of suspension systems with actuator;

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Intelligent Control, Filtering and Model Reduction Analysis for Fuzzy-Model-Based Systems

control and stability analysis, dynamic output feedback control, fault detection filter design, and reduced-order model approximation. Some;

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Intelligent Control, Filtering and Model Reduction Analysis for Fuzzy-Model-Based Systems

control and stability analysis, dynamic output feedback control, fault detection filter design, and reduced-order model approximation. Some;

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Introduction to Fuzzy Systems

fuzzy control theory, based mainly on the well-known classical Proportional-Integral-Derivative (PID) controllers theory and design methods;

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Fuzzy Control Systems

fuzzy control design for a class of nonlinear Markovin jump systems via a LMI-based approach.;

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Sliding Mode Control of Semi-Markovian Jump Systems

This book presents analysis and design for a class of stochastic systems with semi-Markovian jump parameters. It explores systematic;

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Fuzzy Logic Control in Energy Systems with design applications in MATLAB (R)/Simulink (R)

concepts and techniques required for designing fuzzy logic controllers, and then discusses several applications to control and management in energy;

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Monitoring And Control Of Information-Poor Systems

-making and shows how it can be used to design a predictive control scheme that is suitable for controlling information-poor systems using;

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Fuzzy Control of Industrial Systems

Fuzzy Control of Industrial Systems: Theory and Applications presents the basic theoretical framework of crisp and fuzzy set theory;

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Soft Computing with NeuroFuzzy Systems

neuro-fuzzy inference system for optimal design of reinforced concrete beams; comparison between neural network and adaptive neuro-fuzzy;

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Fuzzy Controller Design

Fuzzy control methods are critical for meeting the demands of complex nonlinear systems. They bestow robust, adaptive, and self-correcting;

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Neuro-fuzzy Control of Industrial Systems with Actuator Nonlinearities

Neural networks and fuzzy systems are model free control design approaches that represent an advantage over classical control when dealing;

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Design of GA-Fuzzy Controller for Magnetic Levitation Using FPGA

The design of controllers for non- linear systems in industry is a complex and difficult task. The development of non-linear control;

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Two-Dimensional Systems

and filter design for multidimensional systems, especially multi-dimensional fuzzy systems, will find this book a useful resource as will;

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Two-Dimensional Systems

and filter design for multidimensional systems, especially multi-dimensional fuzzy systems, will find this book a useful resource as will;

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