Institutional Repository
| Adaptive fading Kalman filter with an application | |
| Qijun Xia; Ming Rao; Yiqun Ying; Xuemin Shen | |
| 1994 | |
| Source | Automatica
 |
| Volume | 30Issue:8Pages:1333-1338 |
| English Abstract | A new adaptive state estimation algorithm, namely adaptive fading Kalman filter (AFKF), is proposed to solve the divergence problem of Kalman filter. A criterion function is constructed to measure the optimality of Kalman filter. The forgetting factor in AFKF is adaptively adjusted by minimizing the defined criterion function using measured outputs. The algorithm remains convergent and tends to be optimal in the presence of model errors. It has been successfully applied to the headbox of a paper-making machine for state estimation. |
| Indexed Type | 其他 |
| Cooperation Status | 其它 |
| Keyword | Kalman Filter State Estimation Adaptive Estimation Discrete System Industrial Processes |
| Language | 英语 |
| Content Type | 期刊论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/1341 |
| Collection | 中国科学院软件研究所 |
| Recommended Citation GB/T 7714 | Qijun Xia,Ming Rao,Yiqun Ying,et al. Adaptive fading Kalman filter with an application[J]. Automatica,1994,30(8):1333-1338. |
| APA | Qijun Xia,Ming Rao,Yiqun Ying,&Xuemin Shen.(1994).Adaptive fading Kalman filter with an application.Automatica,30(8),1333-1338. |
| MLA | Qijun Xia,et al."Adaptive fading Kalman filter with an application".Automatica 30.8(1994):1333-1338. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| bj01141591.pdf（463KB） | 开放获取 | License | Application Full Text | |||
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