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Neural Network Control of Nonlinear Discrete-Time Systems

. Progressive Development After an introduction to neural networks, dynamical systems, control of nonlinear systems, and feedback linearization, the;

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Neural Networks Modeling and Control

Neural Networks Modelling and Control: Applications for Unknown Nonlinear Delayed Systems in Discrete Time focuses on modeling and;

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Optimal Networked Control Systems with MATLAB

formulation for linear systems in input-output form enclosed by a communication network Addresses the stochastic optimal control of nonlinear;

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Optimal Networked Control Systems With MATLAB

systems in input-output form enclosed by a communication network Addresses the stochastic optimal control of nonlinear NCS by using neuro dynamic;

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Discrete-Time Recurrent Neural Control

as a deep theoretical analysis of Artificial Neural Networks to control discrete-time nonlinear systems. It is important to remark that first;

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Discrete-Time Recurrent Neural Control

as a deep theoretical analysis of Artificial Neural Networks to control discrete-time nonlinear systems. It is important to remark that first;

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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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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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Adaptive Sliding Mode Neural Network Control for Nonlinear Systems

Adaptive Sliding Mode Neural Network Control for Nonlinear Systems introduces nonlinear systems basic knowledge, analysis and control;

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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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Nonlinear Dynamical Systems

interconnection strengths known as synaptic weights. In Nonlinear Dynamical Systems: Feedforward Neural Network Perspectives, six leading authorities;

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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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Control of Self-Organizing Nonlinear Systems

The book summarizes the state-of-the-art of research on control of self-organizing nonlinear systems with contributions from leading;

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Control of Self-Organizing Nonlinear Systems

The book summarizes the state-of-the-art of research on control of self-organizing nonlinear systems with contributions from leading;

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Advances in Discrete-Time Sliding Mode Control

: Focuses on LMI-based SMC (sliding mode control) for uncertain discrete-time system using novel nonlinear components in the control law;

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Advances in Discrete-Time Sliding Mode Control

: Focuses on LMI-based SMC (sliding mode control) for uncertain discrete-time system using novel nonlinear components in the control law;

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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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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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Nonlinear Stochastic Control and Filtering with Engineering-Oriented Complexities

Nonlinear Stochastic Control and Filtering with Engineering-oriented Complexities presents a series of control and filtering approaches for;

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Nonlinear Stochastic Control and Filtering With Engineering-Oriented Complexities

control problem for a class of dynamical networks with randomly varying nonlinearities Nonlinear Stochastic Control and Filtering with;

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Bifurcation and Nonlinear Dynamics in Neural Network

dynamics and chaos into neural networks. In this book, a new type of neural network is introduced based on the nonlinear dynamics and chaos;

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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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Nonlinear Biomedical Signal Processing

. Akay's Nonlinear Biomedical Signal Processing, Volume I: Fuzzy Logic, Neural Networks, and New Algorithms.;

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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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Nonlinear and Adaptive Control Systems

techniques to analyse nonlinear systems. Therefore it is natural to treat adaptive control as a part of nonlinear control systems. Nonlinear and;

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