Prediction on nonlinear dynamic responds of non-lubrication mechanism system considered friction and flexibleness based on neural network

The characters of flexible mechanism motion are highly nonlinear. The dynamic responds of mechanism become more uncertain because of friction and flexibleness. It is more difficult to control the mechanism at the real time. Via modified Elman dynamical artificial neural network, nonlinear parameters prediction model of non-lubrication mechanism considered influence of friction and flexibleness was established identification model to identify and forecast the motive parameters of flexible mechanism. Expand mechanism of space station was applied to test this method. The results prove that the calculation speed of the model is fast and the precision is high. The methods provide an available way on the control of complicated systems at the real time.