Unscented Transformation Based Robust Kalman Filter and Its Applications in Fermentation Process

王建林; 冯絮影; 赵利强; 于涛

doi:10.1016/S1004-9541(10)60239-X

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Unscented Transformation Based Robust Kalman Filter and Its Applications in Fermentation Process

Updated：2026-01-06

- Unscented Transformation Based Robust Kalman Filter and Its Applications in Fermentation Process
- Unscented Transformation Based Robust Kalman Filter and Its Applications in Fermentation Process
- 中国化学工程学报（英文版） 2010年18卷第3期页码：412-418
- Affiliations：
  
  College of Information Science and Technology, Beijing University of Chemical Technology,Beijing,China,100029
- Author bio：
- Funds：
- DOI：10.1016/S1004-9541(10)60239-X
  中图分类号：
- 纸质出版：2010
- Accepted：
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王建林, 冯絮影, 赵利强, 等. Unscented Transformation Based Robust Kalman Filter and Its Applications in Fermentation Process[J]. 中国化学工程学报（英文版）, 2010,18(3):412-418.

WANG Jianlin, FENG Xuying, ZHAO Liqiang, YU Tao. Unscented Transformation Based Robust Kalman Filter and Its Applications in Fermentation Process[J]. , 2010, 18(3): 412-418.
王建林, 冯絮影, 赵利强, 等. Unscented Transformation Based Robust Kalman Filter and Its Applications in Fermentation Process[J]. 中国化学工程学报（英文版）, 2010,18(3):412-418. DOI： 10.1016/S1004-9541(10)60239-X.

WANG Jianlin, FENG Xuying, ZHAO Liqiang, YU Tao. Unscented Transformation Based Robust Kalman Filter and Its Applications in Fermentation Process[J]. , 2010, 18(3): 412-418. DOI： 10.1016/S1004-9541(10)60239-X.

摘要

Abstract

State estimation is the precondition and foundation of a bioprocess monitoring and optimal control. However

there are many difficulties in dealing with a non-linear system

such as the instability of process

un-modeled dynamics

parameter sensitivity

etc

.This paper discusses the principles and characteristics of three different approaches

extended Kalman filters

strong tracking filters and unscented transformation based Kalman filters.By introducing the unscented transformation method and a sub-optimal fading factor to correct the prediction error covariance

an improved Kalman filter

unscented transformation based robust Kalman filter

is proposed. The performance of the algorithm is compared with the strong tracking filter and unscented transformation based Kalman filter and illustrated in a typical case study for glutathione fermentation process.The results show that the proposed algorithm presents better accuracy and stability on the state estimation in numerical calculations.

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