The paper focuses on the practical benefits of using artificial neural networks (ANNs) in the control of unmanned aircraft vehicles (UAVs) and for the purposes of identification and surveillance. The presented methodology for modeling flight dynamics uses ANNs. Modeling of the object dynamics was based on experimental results obtained during flight tests. The aerodynamic g-loads were derived as a function of the flow parameters. The aim of ANN is to select weights of the neural network in such a way that it simultaneously generates all the necessary parameters to implement into the model with a high fidelity.
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