Robust Estimation for Hammerstein Models Based on Variational Inference

Zhengya Ma, Xiaoxu Wang, Rui Li, Haoran Cui

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

The paper presents a robust identification method using variational inference (VI) for Hammerstein models in the presence of process noise and non-Gaussian colored measurement noise. First of all the measurements and process output are described as Student's t and Gaussian distribution by using introduced variational parameters. Then the conjugate prior information of introduced parameters is framed for sake of a closed-loop solution. By applying the idea of VI, estimates of system parameters are got by minimizing Kullback-Leibler (KL) divergence. Finally, a numerical simulation example is used to show the effectiveness of the proposed identification method compared with the traditional method.

源语言英语
主期刊名Proceedings - 2022 Chinese Automation Congress, CAC 2022
出版商Institute of Electrical and Electronics Engineers Inc.
2716-2721
页数6
ISBN(电子版)9781665465335
DOI
出版状态已出版 - 2022
活动2022 Chinese Automation Congress, CAC 2022 - Xiamen, 中国
期限: 25 11月 202227 11月 2022

出版系列

姓名Proceedings - 2022 Chinese Automation Congress, CAC 2022
2022-January

会议

会议2022 Chinese Automation Congress, CAC 2022
国家/地区中国
Xiamen
时期25/11/2227/11/22

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