@inproceedings{97cc2ba3463f480b97c9d757a925da7b,
title = "ANN-based acceleration harmonic identification for an electro-hydraulic servo system",
abstract = "Since the dead zone phenomenon occurs in electro-hydraulic servo system, the acceleration output of the system corresponding to a sinusoidal input contains higher harmonic besides the fundamental response, causing harmonic distortion of the output acceleration signal. The output wave includes odd harmonics up to 11th harmonic. The method for harmonic identification based on artificial neural network (ANN) is proposed here. This method uses an Adaline neural network to identify the amplitude and phase of harmonics as well as the fundamental acceleration output on-line. The weights of the Adaline are adjusted according to the error between the actual and the estimated acceleration to yield the Fourier coefficients of the output wave. The simulation results show the validity of the analytical results and the ability of the algorithm to on-line identify all harmonics including the fundamental effectively with high accuracy.",
keywords = "Dead zone, Harmonic distortion, Harmonic identification, Neural network, Odd harmonic",
author = "Jianjun Yao and Dacheng Cong and Hongzhou Jiang and Zhenshun Wu and Junwei Han",
year = "2007",
doi = "10.1109/ICITECHNOLOGY.2007.4290505",
language = "英语",
isbn = "1424410924",
series = "IEEE ICIT 2007 - 2007 IEEE International Conference on Integration Technology",
pages = "398--402",
booktitle = "IEEE ICIT 2007 - 2007 IEEE International Conferenceon Integration Technology",
note = "2007 IEEE International Conference on Integration Technology, ICIT 2007 ; Conference date: 20-03-2007 Through 24-03-2007",
}