Nonlinear simulation analysis of a tailless advanced fighter aircraft reconfigurable flight control law

This paper presents nonlinear simulation results from the non real-time evaluation of a reconfigurable flight control law for a tailless advanced fighter aircraft operating under critical failure and damage conditions. The reconfigurable control law combines direct adaptive control, system identification, and optimal control allocation. The reconfigurable control law, which is based on dynamic inversion in an explicit model following f%amework, employs an on-line neural network to adaptively regulate the error in the plant inversion, which may be due to modeling uncertainties, failures, or damage. On-line control allocation is used to generate individual control effector commands which yield the desired rotational accelerations while optimizing performance objectives such as maneuver load alleviation and stealth. On-line system identification provides estimates of the control derivatives used by the control allocation algorithms. Signals are injected into the kernel of the control distribution matrix to allow identification of parameters which are colinear due to the effector ganging resulting from the control allocation algorithms. The results presented in this paper are based on work performed by team+ on the Air Force sponsored program* . Introduction the Boeing RESTORE Reconfigurable flight control refers to the ability of a control system to adapt to unknown failures and + Boeing Phantom Works (St. Louis, MO), Honeywell Technology Center (Minneapolis, MN), Guided Systems Technology (Atlanta, GA), University of Illinois (Champaign Urbana, IL) * Reconfigurable Control for Tailless Aircraft (RESTORE) Program sponsored by Air Force Research Labs, Wright-Patterson APB, OH; Contract No. F33615-96-C-3612 Copyright

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