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Neural Approximations for Optimal Control and Decision

Neural Approximations for Optimal Control and Decision provides a comprehensive methodology for the approximate solution of functional;

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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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Nonlinear Pinning Control of Complex Dynamical Networks

inverse optimal control approach is employed. For both cases, model-based is considered in Chapter 3 and Chapter 5; then, Chapter 4 and Chapter 6;

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Predictions, Nonlinearities and Portfolio Choice

covariance matrix - Optimal portfolio decision making - Nonlinear modeling, performed by artificial neural networks, and their impact on predictions;

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Deep Reinforcement Learning with Guaranteed Performance

This book discusses methods and algorithms for the near-optimal adaptive control of nonlinear systems, including the corresponding;

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Type 2 Fuzzy Neural Networks and Their Applications

of the foundation of type-2 fuzzy neural networks and presents a vast compendium of its applications to control, forecasting, decision making;

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Finite Approximations in Discrete-Time Stochastic Control

In a unified form, this monograph presents fundamental results on the approximation of centralized and decentralized stochastic control;

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Kinematic Control of Redundant Robot Arms Using Neural Networks

Networks for Parallel Robot Control; and Neural Networks for Cooperative Control. The book starts by covering zeroing neural networks for control;

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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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Optimal Control And Forecasting Of Complex Dynamical Systems

This important book reviews applications of optimization and optimal control theory to modern problems in physics, nano-science and finance;

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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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Optimization

optimality conditions for highly complex problems, such as optimal con trol problems with control and trajectory constraints, is much easier;

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Optimal Networked Control Systems with MATLAB

communication network Covers distributed joint optimal network scheduling and control design for wireless NCS, as well as the effect of network;

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Optimal Networked Control Systems With MATLAB

optimal network scheduling and control design for wireless NCS, as well as the effect of network protocols on the wireless NCS controller design;

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Wall Turbulence Control

, optimal and suboptimal control methodology, linear control and control using adaptive methods (neural networks), polymer and bubble injection;

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Discrete-Time Recurrent Neural Control

The book presents recent advances in the theory of neural control for discrete-time nonlinear systems with multiple inputs and multiple;

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Discrete-Time Recurrent Neural Control

The book presents recent advances in the theory of neural control for discrete-time nonlinear systems with multiple inputs and multiple;

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Fuzzy Set Theory and Advanced Mathematical Applications

coverage of the mathematical foundations of the theory, decision making and systems science, and recent developments in fuzzy neural control. The;

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Convex Optimization of Power Systems

is an invaluable resource for students and researchers from industry and academia in power systems, optimization, and control.;

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Intelligent Force and Position Control of 6-DOF Robot Manipulator

The application of Artificial Neural Networks in force and position control systems has increased in recent years, because such usage does;

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Discrete-Time Inverse Optimal Control for Nonlinear Systems

Discrete-Time Inverse Optimal Control for Nonlinear Systems proposes a novel inverse optimal control scheme for stabilization and;

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Discrete-Time Inverse Optimal Control for Nonlinear Systems

Discrete-Time Inverse Optimal Control for Nonlinear Systems proposes a novel inverse optimal control scheme for stabilization and;

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11th World Conference Intelligent System for Industrial Automation WCIS 2020

intelligent control systems, pattern recognition, Industry 4.0, information security, neural computing, fuzzy and evolutionary computation, decision;

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Frontiers Of Intelligent Control And Information Processing

researchers from adaptive/approximate dynamic programming, reinforcement learning, machine learning, neural optimal control, networked systems, and;

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

Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to;

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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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Adaptive Neural Control of Walking Robots

responsible for some excellent engineering and technological solutions in the field of responsive or adaptive control. Adaptive Neural Control;

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