Accession Number:

ADA232013

Title:

An Artificial Neural Network Control System for Spacecraft Attitude Stabilization

Descriptive Note:

Master's thesis

Corporate Author:

NAVAL POSTGRADUATE SCHOOL MONTEREY CA

Personal Author(s):

Report Date:

1990-06-01

Pagination or Media Count:

77.0

Abstract:

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.

Subject Categories:

  • Psychology
  • Manned Spacecraft

Distribution Statement:

APPROVED FOR PUBLIC RELEASE