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Toward Real Time Neural Net Flight ControllersNASA Ames Research Center has an ongoing program in neural network control technology targeted toward real time flight demonstrations using a modified F-15 which permits direct inner loop control of actuators, rapid switching between alternative control designs, and substitutable processors. An important part of this program is the ACTIVE flight project which is examining the feasibility of using neural networks in the design, control, and system identification of new aircraft prototypes. This paper discusses two research applications initiated with this objective in mind: utilization of neural networks for wind tunnel aircraft model identification and rapid learning algorithms for on line reconfiguration and control. The first application involves the identification of aerodynamic flight characteristics from analysis of wind tunnel test data. This identification is important in the early stages of aircraft design because complete specification of control architecture's may not be possible even though concept models at varying scales are available for aerodynamic wind tunnel testing. Testing of this type is often a long and expensive process involving measurement of aircraft lift, drag, and moment of inertia at varying angles of attack and control surface configurations. This information in turn can be used in the design of the flight control systems by applying the derived lookup tables to generate piece wise linearized controllers. Thus, reduced costs in tunnel test times and the rapid transfer of wind tunnel insights into prototype controllers becomes an important factor in more efficient generation and testing of new flight systems. NASA Ames Research Center is successfully applying modular neural networks as one way of anticipating small scale aircraft model performances prior to testing, thus reducing the number of in tunnel test hours and potentially, the number of intermediate scaled models required for estimation of surface flow effects.
Document ID
20010046947
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Jorgensen, C. C.
(NASA Ames Research Center Moffett Field, CA United States)
Mah, R. W.
(NASA Ames Research Center Moffett Field, CA United States)
Ross, J.
(NASA Ames Research Center Moffett Field, CA United States)
Lu, Henry, Jr.
Date Acquired
August 20, 2013
Publication Date
January 1, 1994
Subject Category
Aircraft Stability And Control
Meeting Information
Meeting: IEEE World Congress on Computational Intelligence
Location: Orlando, FL
Country: United States
Start Date: June 28, 1994
End Date: July 2, 1994
Sponsors: Institute of Electrical and Electronics Engineers
Funding Number(s)
PROJECT: RTOP 505-64-52
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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