Abstract
In modern era of aviation technology evolution, unmanned aerial vehicles have proved to be crucial in all fields including military and research. The development of robust control system and successful mission accomplishment requires an meticulous UAV model. The aim of this paper is to lay out an elaborate model estimation scheme using various model structure techniques including Auto-regressive Exogenous, Auto-regressive Moving Average exogenous, Box Jenkin’s, Output Error, and state space and non-linear Auto-regressive Exogenous. The obtained models are then analyzed and compared for best model quality parameters like residual analysis, final prediction error and fit percentages. The efficacy of developed model through proposed model is further validated using simulations data for UAV. Results demonstrate the model’s feasibility as it properly predicts system performance over a broad variety of operating situations. To the best of our knowledge, this is the first time in the literature that a model estimation study for UAV platform with such a wide variety of model structures has been presented.
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