ADAPTIVE NEURAL NETWORK ARCHITECTURE FOR ROBUST RECONFIGURABLE FLIGHT CONTROL

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$49,997.00
Award Year:
1990
Program:
SBIR
Phase:
Phase I
Contract:
n/a
Award Id:
13531
Agency Tracking Number:
13531
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
13766 S Hawthorne Blvd, Hawthorne, CA, 90250
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
James C Smith
(213) 679-2281
Business Contact:
() -
Research Institution:
n/a
Abstract
THE PROPOSED WORK ADDRESSES SPECIFIC ISSUES RELATED TO AIRCRAFT STABILITY DURING CONFIGURATION CHANGES, DAMAGE CONTROL AND CONFIGURATION MANAGEMENT WHICH HAVE RECEIVED INCOMPLETE TREATMENT IN EXISTING AIRCRAFT FLIGHT CONTROLLER SYSTEMS DESIGN. THE APPROACH WE HAVE SELECTED UTILIZES NEURAL NET TECHNOLOGY TO IDENTIFY AND COMPENSATE FOR ADVERSE DYNAMICS WHICH CAN BE ENCOUNTERED DURING OPERATIONAL CONFIGURATION CHANGES CONSEQUENT TO (1) DAMAGE CONTROL, (2) MISSION PROFILE SEGMENT TRANSITION OR (3) TACTICAL MODE CHANGE. ADVANCED SIMULATION TECHNIQUES WILL BE EMPLOYED TO EVALUATE THE POTENTIAL OF SEVERAL ALTERNATIVE NEURAL NET ARCHITECTURES IN IDENTIFICATION AND CONTROL OF ADVERSE PLANT CHARACTERISTICS RESULTING FROM CONFIGURATION CHANGE. EXPERIMENTAL RESULTS WILL BE USED TO SPECIFY A DESIGN STRATEGY FOR A RECONFIGURATION MANAGER WHICH IS SENSITIVE TO MISSION OBJECTIVES AND SITUATIONAL VARIABLES WHILE MAXIMIZING AIRCRAFT PERFORMANCE AND SAFETY DURING RECONFIGURATION.

* information listed above is at the time of submission.

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