@inproceedings{37dd78275a064e2cbbc1f754a731c080,
title = "Flight test results of adaptive controllers in presence of severe structural damage",
abstract = "We present flight test results for adaptive controllers intended to mitigate significant aircraft faults. The adaptive controllers are tested in flight on the Georgia Tech GT Twinstar fuxed wing twin engine aircraft with 25% left wing missing. A Model Reference Adaptive Control (MRAC) architecture employing a Neural Network (NN) as adaptive element is used for inner loop attitude control of the aircraft, and is intended to augment a state dependent outer loop guidance logic. Two adaptive control methods are tested. The first is a proven MRAC based method employing a single hidden layer NN. The second is the recently introduced Derivative Free MRAC (DFMRAC) method. The results establish the feasibility of these methods for ensuring safe autonomous flight in presence of severe structural faults.",
author = "Girish Chowdhary and Johnson, {Eric N.} and Kimbrell, {M. Scott} and Rajeev Chandramohan and Anthony Calise",
note = "Funding Information: This work was supported in part by NSF ECS-0238993 and NASA Cooperative Agreement NNX08AD06A.; AIAA Guidance, Navigation, and Control Conference ; Conference date: 02-08-2010 Through 05-08-2010",
year = "2010",
doi = "10.2514/6.2010-8010",
language = "English (US)",
isbn = "9781600869624",
series = "AIAA Guidance, Navigation, and Control Conference",
booktitle = "AIAA Guidance, Navigation, and Control Conference",
}