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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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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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Multi model Jumping Systems Robust Filtering and Fault Detection

well as higher order moment and neural network-based fault detection methods for multi-model jumping systems, allowing them to grasp the;

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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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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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Control and Filtering of Fuzzy Systems with Switched Parameters

, engineers and researchers in the field of intelligent control. Lastly it is useful for advanced courses focusing on fuzzy modeling, analysis, and;

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Control and Filtering of Fuzzy Systems with Switched Parameters

, engineers and researchers in the field of intelligent control. Lastly it is useful for advanced courses focusing on fuzzy modeling, analysis, and;

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Modelling Optimization and Control of Biomedical Systems

; sensitivity analysis & model reduction; multi-parametric programming and model predictive control; estimation techniques; physiologically-based;

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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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Model Based Fuzzy Control

objective of model based fuzzy control is to use the full range of linear and nonlinear design and analysis methods to design such fuzzy controllers;

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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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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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Model Reduction of Complex Dynamical Systems

kernel-based methods; surrogate modeling for design and optimization, with special emphasis on control and data assimilation; model reduction;

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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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Application Of Dimensional Analysis In Systems Modeling And

. Application of Dimensional Analysis in Systems Modeling and Control Design provides an introduction to the fundamentals of dimensional analysis for;

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Intelligent Information and Database Systems

, technology opportunity, e-learning, and fuzzy intelligent systems; analysis for image, video and motion data in life sciences; real world;

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Intelligent Information and Database Systems

, technology opportunity, e-learning, and fuzzy intelligent systems; analysis for image, video and motion data in life sciences; real world;

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Interpretability of Computational Intelligence Based Regression Models

base system. Finally, based on the analogy of support vector regression and fuzzy models, a three-step model reduction algorithm is proposed to;

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Non-monotonic Approach to Robust H? Control of Multi-model Systems

Non-monotonic Approach to Robust H8 Control of Multi-model Systems focuses on robust analysis and synthesis problems for multi-model;

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Engineering Of Mind

of Mind blends current theory and practice to achieve a coherent model for the design of intelligent systems.;

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Interpolatory Methods for Model Reduction

Dynamical systems are a principal tool in the modeling, prediction, and control of a wide range of complex phenomena. As the need for;

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Robust Filtering and Fault Detection of Switched Delay Systems

in the analysis and control synthesis for switched delay systems, the monograph not only provides a systematic approach to designing the filter;

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Intelligent Information and Database Systems

Analysis, Applications and Technologies for Internet of Things; Intelligent Algorithms and Brain Functions; Intelligent Systems and Algorithms;

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Intelligent Systems

nonlinear systems. Simple and easy to implement, fuzzy systems can be applied to successful modeling and system control. Illustrating how these;

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Model Reduction for Control System Design

practising control engineers and graduates for intelligent use of commercial software modules for model and controller reduction.;

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