Modelling of the dynamics of a gyroscope using artificial neural networks

It this paper, a neural network was utilized in order to create an emulator, which could mimic the behaviour and nonlinear dynamics of a gyroscope with two axes of freedom, subjected to both low- and high-frequency excitation. For this purpose, several known learning methods, such as the gradient and Levenberg-Margquardt method, were used. Three different models of neural networks were considered and compared for their effectiveness: NNFIR, NNARX and the recurrent network NNARMAX.