A self-organizing controller is developed for a simplified two-dimensional aircraft model. The controller learns how to pilot the aircraft through a navigational mission without exceeding pre-established position and velocity limits. The controller pilots the aircraft by activating one of eight directional actuators at all times. By continually monitoring the aircraft's position and velocity with respect to the mission, the controller progressively modifies its decision rules to improve the aircraft's performance. When the controller has learned how to pilot the aircraft, two actuators fail permanently. Despite this malfunction, the controller regains proficiency at its original task. The experimental results reported show the controller's capabilities foe self-organizing control, learning, and malfunction recovery.
Application of Adaptive Learning to Malfunction Recovery
1985
51 pages
Report
Keine Angabe
Englisch
Avionics , Adaptive control systems , Flight control systems , Adaptive training , Learning , Aircraft , Position(Location) , Pilots , Actuators , Directional , Missions , Navigation , Self organizing systems , Monitoring , Decision theory , Aircraft models , Simplification , Two dimensional , Limitations , Velocity , Malfunctions , Recovery , Learning machines
Application of Adaptive Learning to Malfunction Recovery
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