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.