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Danger Management: Intelligent Software Promises to Make Flying Safer

Highly-modified F-15B Intelligent Flight Control System research aircraft

Photo left: NASA's highly-modified F-15B IFCS research aircraft flies above Roger's Dry Lake at Edwards Air Force Base in Southern California. NASA photo by Jim Ross

NASA researchers are developing revolutionary computer tools that might enable future aircraft suffering major system failures or combat damage to be flown to a safe, controlled landing.

Flying aboard a highly-modified NASA F-15B aircraft, the computer system and software, known as the Intelligent Flight Control System (IFCS), focuses on development of "self-learning" neural network software for aircraft flight control computers.

In its final form, the system's software would calculate the actions required to enable a damaged aircraft to continue flying safely, then automatically adjust the flight controls to compensate for the damage.

Recently, the IFCS project team successfully met milestone research objectives by evaluating in flight a passive online Parameter Identification, (PID) algorithm, or software code, and an online learning Dynamic Cell Structure, or DCS, neural net algorithm.

The project team assessed the ability of the PID and DCS algorithms to efficiently identify aircraft stability and control characteristics, and map and retain this information.

"This work marks a significant step toward learning, thinking, aircraft that will be safer, more autonomous, and more reliable than ever before," says John Carter, the NASA Dryden Flight Research Center's IFCS project manager.

This is a major step for real time PID and neural net technology, and serves as proof of technology for the project's Generation I flight control concept.

The PID algorithm is an online function that determines the actual stability and control characteristics of the aircraft as it flies. When results from the PID algorithm differ from what is called the pre-trained neural network, or PTNN, an update to the system is required.

The Dynamic Cell Structure provides the online learning of the system. It tracks the differences between the PTNN and PID and provides an organized map of updates to the stability and control derivatives of the aircraft.

NASA's Ames Research Center developed the DCS software for Generation I direct adaptive application. The PID software was developed by the Institute for Scientific Research in conjunction with NASA's Langley Research Center.

Included among important features of the DCS are the facts that it has long-term memory, critical for IFCS use, and the network has the ability to be enlarged by the addition of nodes.

Photo right: With a distinctive color scheme, NASA's highly-modified F-15B IFCS research aircraft soars in the California sky. NASA photo by Jim Ross

Highly-modified F-15B Intelligent Flight Control System research aircraft

IFCS software evaluations performed by the F-15B aircraft included handling qualities maneuvers, envelope boundary maneuvers, control surface excitations for real-time PID to include pitch, roll, and yaw, and neural network performance.

The IFCS team includes: NASA Dryden Flight Research Center, Edwards, Calif., Ames Research Center, Moffett Field, Calif., NASA's Langley Research Center, Hampton, Va., Boeing Phantom Works, St. Louis, Mo., and in Fairmont, W. Va.

Story by Gray Creech, Public Affairs, NASA Dryden Flight Research Center

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Last Updated: November 30, 2007
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