@inproceedings{8e90f2b4e7584ce98f684c347e5acf24,
title = "Adaptive uncerntainty identification with neural network",
abstract = "This paper provides an identification method for uncertainties in system via dynamic neural networks, where the uncertainties include parameter uncertainty, disturbances, faults or system load. The incertainties here are translated into the weight matrices to be identified. To idenfication purpose, a dynamic neural network observer is designed, where weight matrices are adaptive tuned. The numerical simulation shows that the given idenificatuion algorithm is more suitable for disturbances, faults or system load. For given system load, the present algorithm can model system into multimodel mode.",
keywords = "Adaptive Learning, Neural Network, Observer",
author = "Yumin Zhang and Fei Teng and Guiqin Liang and Zhiqiang Wang",
note = "Publisher Copyright: {\textcopyright} 2015 Technical Committee on Control Theory, Chinese Association of Automation.; 34th Chinese Control Conference, CCC 2015 ; Conference date: 28-07-2015 Through 30-07-2015",
year = "2015",
month = sep,
day = "11",
doi = "10.1109/ChiCC.2015.7259948",
language = "英语",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "2055--2059",
editor = "Qianchuan Zhao and Shirong Liu",
booktitle = "Proceedings of the 34th Chinese Control Conference, CCC 2015",
address = "美国",
}