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This work proposes the use of hybrid models of supervised neural networks for modeling of a dynamical complex system and analyze different training architectures, in this case a scale helicopter, whose attitude and position identification is performed. This model will be useful for the development and utilization of the helicopter as unmanned aerial vehicle (UAV). Throughout this work the supervised...
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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