Identification of Non-Dimensional Aerodynamic Derivatives using Markov Parameter Based Least Squares Identification Algorithm

Direct identification of non-dimensional stability & control derivatives is necessary for the flight vehicle modeling process. Estimates of the derivatives are obtained by using the computed Markov Parameters, or the pulse response of a system, with a least squares estimator. The developed approach is then demonstrated against the standard Equation Error and Output Error method to identify the short period dynamics of a small fixed-winged Unmanned Air Systems using experimental flight data. It is shown that the developed approach is able to generate a model of similar quality to the Output Error method according to the averaged Theil Inequality Coefficient. It is also demonstrated that the developed approach combined with the Output Error method generates the same model as the combined Equation Error/Output Error approach while reducing the computation time.