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Model-Based Tracking Control of Nonlinear Systems

Model-Based Control of Nonlinear Systems presents model-based control techniques for nonlinear, constrained systems. It covers constructive;

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Model-Based Tracking Control of Nonlinear Systems

Model-Based Control of Nonlinear Systems presents model-based control techniques for nonlinear, constrained systems. It covers constructive;

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Techniques of Model-Based Control

A comprehensive introduction to the concepts, techniques, and applications of model-based process control that presents the process control;

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Control Oriented Modelling & Identificat

-based model reduction techniques; integrated modelling and parameter estimation; identification for robust control of complex systems; subspace;

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Learning-Based Adaptive Control

maintained. Includes a good number of Mechatronics Examples of the techniques.Compares and blends Model-free and Model-based;

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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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Model-Based Fault Diagnosis Techniques

mathematical and control-theoretic tools. This second edition of Model-Based Fault Diagnosis Techniques contains: * new material on fault isolation;

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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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Advanced Control of Chemical Processes

industries. New adaptive, statistical, model-based control and artificial intelligence techniques and their applications are detailed in several;

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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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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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Optimal State Estimation for Process Monitoring, Fault Diagnosis and Control

Optimal State Estimation for Process Monitoring, Fault Diagnosis and Control presents various mechanistic model based state estimators;

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Active Sound and Vibration Control

tuning, model-based control design for active vibration control (AVC), ASVC using neural networks, genetic algorithms for ASVC systems, and;

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Model-based Nonlinear Control of Aeroengines

This book aims to develop systematic design methodologies to model-based nonlinear control of aeroengines, focusing on (1) modelling;

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Model Predictive Control for Doubly-Fed Induction Generators and Three-Phase Power Converters

techniques, introduce the utility of model predictive control, review core concepts of vector control, direct torque control, and direct power;

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Model Reduction of Complex Dynamical Systems

time-dependent problems. Chapters are written by leading researchers and users of model order reduction techniques and are based on;

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Computer-Based Industrial Control

control. The control techniques covered include classical controls as well as newer controls such as model-based adaptive control, self-tuning;

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Model Predictive Control

-based PID control, genetic algorithm optimization-based model predictive control, and industrial applications. Providing important insights;

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Nonlinear Control for Blood Glucose Regulation of Diabetic Patients: An LMI Approach

the first book on LMI-based nonlinear control techniques for the Artificial Pancreas;

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Self-Learning Optimal Control of Nonlinear Systems

This book presents a class of novel, self-learning, optimal control schemes based on adaptive dynamic programming techniques, which;

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Model-Based Control

Model-Based Control will be a collection of state-of-the-art contributions in the field of modelling, identification, robust control and;

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INDUCTION MOTORS Dynamics and Vector Control

controllers, the direct torque control systems (DTC) are based on the space angle of the stator flux, on the dynamic model of the induction motor in a;

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Practical Model-Based Testing

testingHow to use a variety of test selection criteria to control the tests that are generated from your modelsHow model-based;

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Voltage Control Based on Fuzzy Adaptive Particle Swarm Optimization

in rescheduling of the reactive power flow in the lines of power system. Despite the fact that many voltage-control techniques are available to electric;

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Model Predictive Control

techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The;

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