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Published online by Cambridge University Press: 03 February 2016
Even small differences in atmospheric and/or flight conditions can potentially impact significantly the evaluation of the performance of the control laws and prevent a correct comparison, especially in the case of reduced size aircraft (autonomous or remotely piloted). Consistent deterministic control inputs can only be guaranteed through some form of computer-based on-board excitation system. In this paper, a methodology is proposed for flight data reduction with the purpose of accounting for non-homogeneous atmospheric conditions and inconsistent pilot inputs. The method is developed for the specific purpose of comparing model-following adaptive control laws. Performance evaluation parameters based on angular rate tracking errors are defined and used for the comparison. As a result of this approach, an additive correction is applied to the angular rate measurements to compensate for non-homogeneous turbulence effects. A multiplicative correction factor is applied to the angular rate tracking error to take into account non-identical pilot inputs. The procedure is validated with simulation and flight data obtained in the process of designing a set of fault tolerant control laws based on non-linear dynamic inversion with neural network augmentation for the reduced size WVU YF-22 aircraft model.