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Model Free Adaptive Fuzzy Control

of such processes. The book discusses one particular approach to the fuzzy controllers. Adaptive Model Free Fuzzy Control is a goal oriented;

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Soft Computing with NeuroFuzzy Systems

-fuzzy systems, neuro-fuzzy inference systems, and neuro-fuzzy control. Section 1 focuses on intelligent neuro-fuzzy models, describing fuzzy;

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Analysis and Synthesis of Fuzzy Control Systems

success as an alternative to conventional control techniques. However, because it is fundamentally model free, conventional FLC suffers from a;

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Analysis and Synthesis of Fuzzy Control Systems

success as an alternative to conventional control techniques. However, because it is fundamentally model free, conventional FLC suffers from a;

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Data-Driven Model-Free Controllers

adaptive-Virtual Reference Feedback Tuning controllers, hybrid model-free and model-free adaptive fuzzy controllers and cooperative model-free;

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Model Free Adaptive Control

Model Free Adaptive Control: Theory and Applications summarizes theory and applications of model-free adaptive control (MFAC). MFAC is a;

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Model Free Adaptive Control

Model Free Adaptive Control: Theory and Applications summarizes theory and applications of model-free adaptive control (MFAC). MFAC is a;

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System Identification and Adaptive Control

research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented. Both;

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Modern Control Engineering

recent methods in system identification and optimal, digital, adaptive, robust, and fuzzy control, as well as stability, controllability;

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Learning-Based Adaptive Control

new perspective about how to deal with these variations. By merging together Model-Free and Model-Based learning algorithms, the author;

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Virtual Equivalent System Approach for Stability Analysis of Model-based Control Systems

. In closing, the VES concept and methodology are used to assess the stability of multiple model adaptive control (MMAC) systems and T-S model-based;

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Virtual Equivalent System Approach for Stability Analysis of Model based Control

. In closing, the VES concept and methodology are used to assess the stability of multiple model adaptive control (MMAC) systems and T-S model-based;

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Voltage Control Based on Fuzzy Adaptive Particle Swarm Optimization

the mathematical model that represents the voltage- control problem of a power system. The purpose is to ensure acceptable voltage profile and;

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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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Fuzzy Control Systems Design And Analysis

A comprehensive treatment of model-based fuzzy control systems This volume offers full coverage of the systematic framework for the;

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Fuzzy Control and Identification

unknown models. Finally, fuzzy modeling and control methods are combined in the book, to create adaptive fuzzy controllers, ending with an example;

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Adaptive Control

controller for multi-robot systems; L1 adaptive control design of the the longitudinal dynamics of a hypersonic vehicle model; adaptive high-gain;

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Control Systems

mathematical foundation of control theory of linear, nonlinear, optimal, model predictive, robust, digital, and adaptive control systems, and it;

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Neuro-Fuzzy Equalizers for Mobile Cellular Channels

Equalizers are present in all forms of communication systems. Neuro-Fuzzy Equalizers for Mobile Cellular Channels details the modeling of a;

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Neuro-Fuzzy Equalizers for Mobile Cellular Channels

Equalizers are present in all forms of communication systems. Neuro-Fuzzy Equalizers for Mobile Cellular Channels details the modeling of a;

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Intelligent Adaptive Control: Industrial Applications

application of intelligent control, particularly employing fuzzy logic, neural networks, and evolutionary computing.;

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

control, model reduction, and fault detection of fuzzy systems, and is also a useful source of information for senior undergraduates and graduates;

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

control, model reduction, and fault detection of fuzzy systems, and is also a useful source of information for senior undergraduates and graduates;

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Modelling, Simulation and Control of Non-linear Dynamical Systems

These authors use soft computing techniques and fractal theory in this new approach to mathematical modeling, simulation and control;

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