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By Omid Omidvar, University of the District of Columbia David Elliott, Institute of Systems Research, University of Maryland
Description Control problems offer an industrially important application and a guide to understanding control systems for those working in Neural
Networks. Neural Systems for Control represents the most up-to-date developments in the rapidly growing aplication area
of neural networks and focuses on research in natural and artifical neural systems directly applicable to control or making use of modern
control theory. The book covers such important new developments in control systems such as intelligent sensors in semiconductor wafer
manufacturing; the relation between muscles and cerebral neurons in speech recognition; online compensation of reconfigurable control
for spacecraft aircraft and other systems; applications to rolling mills, robotics and process control; the usage of past output data
to identify nonlinear systems by neural networks; neural approximate optimal control; model-free nonlinear control; and neural control
based on a regulation of physiological investigation/blood pressure control. All researchers and students dealing with control systems
will find the fascinating Neural Systems for Control of immense interest and assistance.
Audience
Researchers and practicioners in the fields of neural networks, control engineering, mechanical engineering, and electrical engineering.
Contents Introduction: Neural Networks and Automatic Control. Reinforcement Learning. Neurocontrol in Sequence Recognition. A Learning Sensorimotor
Map of Arm Movements: A Step Toward Biological Arm Control. Neuronal Modeling of the Baroceptor Reflex with Applications in Process Modeling
and Control. Identification of Nonlinear Dynamical Systems Using Neural Networks. Neural Network Control of Robot Arms and Nonlinear
Systems. Neual Networks for Intelligent Sensors and Control-PracticalIssues and Some Solutions. Approximation of Time-Optimal Control
for an Industrial Production Plant with General Regression Neural Network. Neuro-Control Design: Reconfigurable Neural Control in Precision
Space Structural Platforms. Neural Approximationsfor Finite- and Infinite-Horizon Optimal Control. Index.
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