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Adaptive Approximation Based Control

A highly accessible and unified approach to the design and analysis of intelligent control systems Adaptive Approximation Based Control;

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Adaptive Stochastic Methods

of Adaptive Integration Based on Piecewise Approximation Methods of Adaptive Integration Based on Global Approximation Numerical Experiments;

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Adaptive IIR Filtering in Signal Processing and Control

Integrates rational approximation with adaptive filtering, providing viable, numerically reliable procedures for creating adaptive infinite;

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Radial Basis Function (RBF) Neural Network Control for Mechanical Systems

stable adaptive control system design using neural network approximation-based techniques. The main objectives of the book are to introduce the;

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Robust Adaptive Control for Fractional-Order Systems with Disturbance and Saturation

. Based on the approximation ability of the neural network (NN), the adaptive neural control schemes are reported for uncertain fractional-order;

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End-to-End Adaptive Congestion Control in TCP/IP Networks

presents a parallel examination of specific adaptive congestion control, NNRC, using adaptive control and approximation theory, as well as;

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Multi-Agent Systems

control (SMC) algorithms are proposed to guarantee strong string stability based on modified constant time headway (MCTH) policy. The MCTH policy;

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Multi-Agent Systems

control (SMC) algorithms are proposed to guarantee strong string stability based on modified constant time headway (MCTH) policy. The MCTH policy;

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Adaptive Control Of Robot Manipulators

This book introduces an unified function approximation approach to the control of uncertain robot manipulators containing general;

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Adaptive Control

sliding mode control for under-actuated mechanical systems; neural network adaptive PID control design based on PLC for a water-level system; and;

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Learning-Based Adaptive Control

active research frontier. This book focuses on a specific subclass of adaptive control, namely, learning-based adaptive control. As systems;

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Hamilton-Jacobi-Bellman Equations

Viability approach to simulation of an adaptive controller Galerkin approximations for the optimal control of nonlinear delay differential;

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Soft Computing with NeuroFuzzy Systems

system in speed control of induction motor drives; neuro-fuzzy based interline power flow controller for real time power flow control;

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Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems

network-based control schemes. Each chapter starts with a concise introduction to the problem under study, and a neural network-based control;

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Adaptive RF Front-Ends for Hand-held Applications

knowledge on matching network properties, in order to simplify robust 2-dimensional control. A generic protection concept is presented, based on;

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Adex Optimized Adaptive Controllers and Systems

adaptive control from a perspective of stability, including the latest methodology of adaptive predictive expert (ADEX) control. ADEX Optimized;

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Adaptive Control Design And Analysis

A systematic and unified presentation of the fundamentals of adaptive control theory in both continuous time and discrete time Today;

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Adaptive Control of Nonaffine Systems for Flight Applications

Due to the nonlinear-in-control nature of the dynamical system in aggressive flight maneuvers, well-known dynamic inversion methods cannot;

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Adaptive Bandwidth Management for ATM-Based Broadband Networks

Supporting diverse applications with various Quality-of-Service guarantees in ATM-based broadband networks requires the design of a proper;

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Distributed Cooperative Control and Communication for Multi agent Systems

rigid body systems. The model-based and data-driven control method are employed to design the (optimal) cooperative control protocol. The;

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Distributed Cooperative Control and Communication for Multi agent Systems

rigid body systems. The model-based and data-driven control method are employed to design the (optimal) cooperative control protocol. The;

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Proceedings of 2017 Chinese Intelligent Automation Conference

control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control;

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Underwater Vehicles Design and Applications

vehicle dynamics. The authors investigate the performances of different control schemes, from non-model-based to model-based and adaptive model;

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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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Intelligent Control

as in temperature control for air heater systems with transportation delay, vision-based navigation of mobile robots, intelligent control;

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Deep Reinforcement Learning with Guaranteed Performance

control method based on the Taylor expansion, neural networks, estimator design approaches, and the idea of sliding mode control, focusing on the;

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