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Neural Networks Modeling and Control

control of discrete-time unknown nonlinear delayed systems under uncertainties based on Artificial Neural Networks. First, a Recurrent High Order;

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Discrete-Time Recurrent Neural Control

based on sliding modes and inverse optimal control scheme. This book on Discrete-time Recurrent Neural Control is unique in the literature;

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Discrete-Time Recurrent Neural Control

based on sliding modes and inverse optimal control scheme. This book on Discrete-time Recurrent Neural Control is unique in the literature;

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Neural Network Control of Nonlinear Discrete-Time Systems

neural networks offer a combination of adaptability, parallel processing, and learning capabilities that outperform other intelligent control;

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Discrete-Time Inverse Optimal Control for Nonlinear Systems

book also proposes the use of recurrent neural networks to model discrete-time nonlinear systems. Combined with the inverse optimal control;

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Discrete-Time Inverse Optimal Control for Nonlinear Systems

book also proposes the use of recurrent neural networks to model discrete-time nonlinear systems. Combined with the inverse optimal control;

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Discrete-Time Neural Observers

developed in discrete-time using recurrent high order neural networks in order to design the neural observers, and the online training of the;

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Robust Discrete-Time Flight Control of UAV with External Disturbances

proposed integer-order discrete-time control schemes are based on the designed discrete-time disturbance observers (DTDOs) and the neural network;

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Robust Discrete Time Flight Control of UAV with External Disturbances

proposed integer-order discrete-time control schemes are based on the designed discrete-time disturbance observers (DTDOs) and the neural network;

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Recurrent Neural Networks

This textbook provides a compact but comprehensive treatment that provides analytical and design steps to recurrent neural networks from;

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Neural Network Control Of Robots And Nonlinear Systems

. The first chapter provides a background on neural networks and the second on dynamical systems and control. Chapter three introduces the robot;

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Advances in Neural Networks - ISNN 2016

cover many topics of neural network-related research including signal and image processing; dynamical behaviors of recurrent neural networks;

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LSTM Recurrent Neural Networks for Signature Verification

The author investigated the application of Long Short-Term Memory (LSTM) Recurrent Neural Networks (RNNs) to the task of signature;

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Discrete-Time Stochastic Sliding Mode Control Using Functional Observation

This book extrapolates many of the concepts that are well defined for discrete-time deterministic sliding-mode control for use with;

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Discrete-Time Stochastic Sliding Mode Control Using Functional Observation

This book extrapolates many of the concepts that are well defined for discrete-time deterministic sliding-mode control for use with;

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Advanced Sliding Mode Control for Mechanical Systems

, neural sliding mode control, backstepping sliding mode control, dynamic sliding mode control, sliding mode control based on observer, terminal;

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Discrete-Time Sliding Mode Control

Sliding mode control is a simple and yet robust control technique, where the system states are made to confine to a selected subset;

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Stability Analysis and State Estimation of Memristive Neural Networks

In this book, the stability analysis and estimator design problems are discussed for delayed discrete-time memristive neural networks;

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Optimal Networked Control Systems with MATLAB

engineers, Optimal Networked Control Systems with MATLAB (R) instills a solid understanding of neural network controllers and how to build them.;

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Optimal Networked Control Systems With MATLAB

Optimal Networked Control Systems with MATLAB (R) discusses optimal controller design in discrete time for networked control systems (NCS;

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Analysis and Synthesis of Polynomial Discrete-Time Systems

control systems. The book deals with the application of Sum of Squares techniques in solving specific control and filtering problems that can be;

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Recurrent Neural Networks for Temporal Data Processing

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Cooperative Control Of Multi-Agent Systems

cooperative control is introduced and neural adaptive design techniques for multi-agent nonlinear systems with unknown dynamics, which are rarely;

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Discrete-Time Higher Order Sliding Mode

-time higher order sliding mode. The authors propose a definition of discrete-time higher order sliding mode and a control law is designed by;

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Advances in Discrete-Time Sliding Mode Control

The focus of this book is on the design of a specific control strategy using digital computers. This control strategy referred to as;

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Advances in Discrete-Time Sliding Mode Control

The focus of this book is on the design of a specific control strategy using digital computers. This control strategy referred to as;

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Infinite-Horizon Optimal Control in the Discrete-Time Framework

In this book the authors take a rigorous look at the infinite-horizon discrete-time optimal control theory from the viewpoint;

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