@inproceedings{dbbc2144e1b043079527e97d50c063ab,
title = "Parameter identification of reaction wheel disturbance model based WLS-SVR method",
abstract = "In order to predict the micro-vibration disturbance of reaction wheel, an improved experience model has been provided, which expresses the effect of the reaction wheel's natural frequencies being the dominating factor in amplifying the disturbance. WLS-SVR algorithm is applied to identify the parameters of this model. The robust characteristic of this algorithm promises the global optimal estimation can be achieved. Experiment has been set up to measure the disturbance of the reaction wheel. Data achieved from the experiment are used to get the parameters of model and verify the identification results of WLS-SVR algorithm. The results show the improved model describes the properties of disturbance more precisely and the WLS-SVR algorithm can achieve accurately identification results.",
keywords = "Disturbance model, Micro-vibration, Natural frequency, Reaction wheel, WLS-SVR",
author = "Wang, \{Yun Feng\} and Wei Cheng and Xia, \{Ming Yi\} and Shuang Wu",
year = "2013",
doi = "10.4028/www.scientific.net/AMM.421.144",
language = "英语",
isbn = "9783037858783",
series = "Applied Mechanics and Materials",
pages = "144--149",
booktitle = "Information Technology for Manufacturing Systems IV",
note = "4th International Conference on Information Technology for Manufacturing Systems, ITMS 2013 ; Conference date: 28-08-2013 Through 29-08-2013",
}