scope:

Abstract:

The NASA F-15 Intelligent Flight Control System (IFCS) project team has developed a series of flight control concepts designed to demonstrate the benefits of a neural network-based adaptive controller. The objective of the team is to develop and flight-test control systems that use neural network technology to optimize the performance of the aircraft under nominal conditions as well as stabilize the aircraft under failure conditions. Failure conditions include locked or failed control surfaces as well as unforeseen damage that might occur to the aircraft in flight. The IFCS team is currently in the process of implementing a second generation control scheme, collectively known as Gen 2, for flight testing on the NASA F-15 aircraft.

The research controller is a dynamic inverse controller based on the Versatile Control Augmentation System (VCAS) control laws developed by James Buckley at McDonnell Douglas Aircraft. The baseline control laws were taken from the F-15 ACTIVE ILTV program, but the IFCS team has removed the thrust vectoring controls for the Gen 2 implementation. For the original dynamic inverse controller, the proportional, integral, & derivative (PID) gains were tuned to achieve linear stability robustness, ASE mode attenuation, and non-linear system command following for the nominal (no failure) case.