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Neural Networks for Control

https://doi.org/10.1007/springerreference_117344

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Adaptive Neurocontrol of a Certain Class of MIMO Discrete-Time Processes Based on Stability Theory

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Study Movement Selection and Synergies via a Synthesized Neuro-Optimization Framework

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Basal Ganglia Perform Differencing Between ‘Desired’ and ‘Experienced’ Parameters

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Case Example 1: Motor incipient fault detection using artificial neural network and fuzzy logic technologies

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Evolutionary Learning in Neural Fuzzy Control Systems

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Approximate Dynamic Programming

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... in der Robotereinsatzplanung

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Efficient State-Space Representation by Neural Maps for Reinforcement Learning

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Introduction — Control Aspects

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Learning in Control Engineering

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Dynamic Local Linear Neuro-Fuzzy Models

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Decentralized Fuzzy-Neural Identification and I-Term Adaptive Control of Distributed Parameter Bioprocess Plant

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Selecting the Best Significant Fragment to the Incremental Heteroassociative Neural Network (RHI)

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A Bio-Inspired Robotic Mechanism for Autonomous Locomotion in Unconventional Environments

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Modular Neural Architectures for Robotics

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Mobile Robot Control Using BP Based Adaptive Critics

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An Improved Method in Receding Horizon Control with Updating of Terminal Cost Function

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One Dimensional IIR Digital Filter Modeling Based on Recurrent Neural Network

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One Approach for Training of Recurrent Neural Network Model of IIR Digital Filter

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On the Structure and Learning of Neural-Network-Based Fuzzy Logic Control Systems

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On the Double Plasticity of Complex Adaptive Systems

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Parameter Identification of Dynamical Systems using Neural Networks

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Control Strategy of Robotic Manipulator Based on Flexible Neural Network Structure

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An Introduction to Neural Networks

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Outline for a Theory of Motor Learning

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Intelligent Control Using Artificial Neural Networks and Fuzzy Logic: Recent Trends and Industrial Applications

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Control of Robotic Manipulators Using Neural Networks — A Survey

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Fuzzy Adaptive Control Versus Model Reference Adaptive Control of Mutable Processes

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Learning to Perceive and Act by Trial and Error

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Performance improvement of robot continuous-path operation through iterative learning using neural networks

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Neural state estimation and prediction in amino acid fermentation

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A computational model of four regions of the cerebellum based on feedback-error learning

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Adaptive feedback control models of the vestibulocerebellum and spinocerebellum

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Learning combined feedback and feedforward control of a musculoskeletal system

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Genetic reinforcement learning for neurocontrol problems

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Enhancing neural control systems by fuzzy logic and evolutionary reinforcement

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Process identification and control

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Structural level comparison of two basic paradigms in neural computation

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Efficient Evolution Strategies for Exploration in mobile robotics

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A memory-based approach to sensory-motor coordination

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Performance evaluation of metamodelling methods for engineering problems: towards a practitioner guide

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Spiking networks as efficient distributed controllers

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A model of the cerebellum in adaptive control of saccadic gain

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Impulse activated sparse cell array network in non-linear autoregressive process modeling

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Stabilization of a class of nonlinear control systems via a neural network scheme with convergence analysis

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Robust control of nonlinear stochastic systems by modelling conditional distributions of control signals

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Discrete time neuro sliding mode control with a task-specific output error

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The finite-horizon optimal control for a class of time-delay affine nonlinear system

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Dual iterative adaptive dynamic programming for a class of discrete-time nonlinear systems with time-delays

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Stable iterative adaptive dynamic programming algorithm with approximation errors for discrete-time nonlinear systems

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Generalized self-tuning regulator based on online support vector regression

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Neural network applications in fault diagnosis and detection: an overview of implementations in engineering-related systems

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An Application of a Neural Self-Tuning Controller to an Overhead Crane

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Perspectives of approximate dynamic programming

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Adaptive Aircraft Flight Control Simulation Based on an Artificial Immune System

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An Adaptive Neural Sliding Mode Controller for MIMO Systems

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Reinforcement learning in feedback control

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Safety-Critical Support Vector Regressor Controller for Nonlinear Systems

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Online Support Vector Regression Based Adaptive NARMA-L2 Controller for Nonlinear Systems

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Universal enzymatic numerical P systems with small number of enzymatic variables

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Approximate dynamic programming solutions with a single network adaptive critic for a class of nonlinear systems

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A review of stochastic algorithms with continuous value function approximation and some new approximate policy iteration algorithms for multidimensional continuous applications

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Geomorphology-based Time-Lagged Recurrent Neural Networks for runoff forecasting

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