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<p>This document reports the results of research into the application of artificial neural networks to controlling dynamic systems. The network used is a feed-forward, fully-connected, 3-layer perception. Two methods of training neural networks via error back-propagation were used. Pattern matching training is a direct method that teaches the basic response. Performance index training is a new technique that refines the response. Performance index training is based on the concept of enforced performance. A neural network will learn to meet a specific performance goal if the performance standard is the only solution to a problem. Performance index training is devised to teach the neural network the time-optimal control law for the system. Real-time adaptation of a neural network in closed loop control of the CrewEquipment Retriever was demonstrated in computer simulations.
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<br>Subjects: Space vehicles.; Neural Networks; Attitude Stabilization; Pattern Matching Training; Time-Optimal Control Law; Performance Index Training</div>
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Segura, Clement M.</div>
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