Unmanned aerial vehicle (UAV) modelling based on supervised neural networks

This paper proposes the utilization of hybrid models of supervised neural networks for the modelling of dynamic systems. Particularly, as an example of a system, an autonomous helicopter or UAV is identified in both attitude and position systems. The evaluation of the model is done by comparing the radial basis and multilayer perceptron with the real system

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