preprints.org > engineering > aerospace engineering > doi: 10.20944/preprints202312.1547.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 19 December 2023 / Approved: 20 December 2023 / Online: 20 December 2023 (13:49:48 CET)

This work proposes a physics-based identification technique based on genetic algorithms. The main objective is to obtain a parametric matrix A that describes the time-invariant linear model of the longitudinal dynamics of an aircraft. This is achieved by proposing a fitness function based on the properties of the transition matrix and taking advantage of some of the capabilities of the genetic algorithm, mainly those of restricting the search ranges of the unknowns. In this case, such unknowns are related to the type of aircraft and flight conditions that are considered during the identification process. The proposed identification method is validated with a reliable nonlinear model that can be found in the literature, as well as with the calculation of the trim condition and linearization generally used in aircraft dynamics. In summary, this study suggests the genetic algorithm provided with the adequate fitness function, could be an appealing alternative for aircraft model identification, even when only a limited amount of data is available. Furthermore, in some cases, linearization using genetic algorithm can be more efficient than classical methods.

Physical-based modelling; system identification; transition matrix; genetic algorithm.

Engineering, Aerospace Engineering

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