@inproceedings{cea3a555ed324d27bd8ab690df58f946,
title = "Mechanical resonance modeling and forecasting in servo systems based on vector fitting",
abstract = "The transmission mechanisms in servo systems have finite stiffness, therefore the elastic deformation and the rotary inertia would cause mechanical resonance in servo systems. Based on the theoretical analysis of the mechanical resonance, the quantitative relation between transfer function of the resonance and system parameters (including torsional elastic coefficient and load rotary inertia) is built. In this paper, the rational approximation of mechanical resonance amplitudefrequency characteristics is calculated by vector fitting method in the presence of known system parameter. With different given system parameters, the nonlinear mapping between system parameters and the transfer function of mechanical resonance through sample training is established through sample training. Therefore, the effective prediction of the transfer function of mechanical resonance with regards to the variation of servos conditions can be realized.",
keywords = "BP neural network, Mechancal resonance, Servo systemis, Vector fitting",
author = "Rui Li and Xuemei Ren",
year = "2013",
doi = "10.1109/MAEE.2013.26",
language = "English",
isbn = "9780769549750",
series = "Proceedings - 2013 International Conference on Mechanical and Automation Engineering, MAEE 2013",
pages = "66--69",
booktitle = "Proceedings - 2013 International Conference on Mechanical and Automation Engineering, MAEE 2013",
note = "2013 International Conference on Mechanical and Automation Engineering, MAEE 2013 ; Conference date: 21-07-2013 Through 23-07-2013",
}