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

作者：Wang Jianlin^*; Feng Xuying; Zhao Liqiang; Yu Tao

来源：Chinese Journal of Chemical Engineering, 2010, 18(3): 412-418.

DOI：10.1016/S1004-9541(10)60239-X

• robust Kalman filter
• unscented transformation
• fermentation process
• nonlinear system

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.

• 出版日期2010-6
• 单位北京化工大学