Nonlinear state estimation for fermentation process using cubature Kalman filter to incorporate delayed measurements

• Published in: Chinese journal of chemical engineering 2015-11, Vol.23 (11), p.1801-1810
• Main Authors: Zhao, Liqiang, Wang, Jianlin, Yu, Tao, Chen, Kunyun, Liu, Tangjiang
• Format: Article
• Language: English
• Subjects: Cubature Kalman filter; Delayed measurements; Fermentation process; Nonlinear state estimation; Sample-state augmentation; 卡尔曼滤波器; 发酵过程; 容积; 延迟测量; 控制性能; 状态估计方法; 状态空间模型; 非线性
• ISSN: 1004-9541; 2210-321X
• DOI: 10.1016/j.cjche.2015.09.005

State estimation of biological process variables directly influences the performance of on-line monitoring and op- timal control for fermentation process. A novel nonlinear state estimation method for fermentation process is proposed using cubature Kalman filter （CKF） to incorporate delayed measurements. The square-root version of CI（F （SCKF） algorithm is given and the system with delayed measurements is described. On this basis, the sample-state augmentation method for the SCKF algorithm is provided and the implementation of the proposed algorithm is constructed. Then a nonlinear state space model for fermentation process is established and the SCKF algorithm incorporating delayed measurements based on fermentation process model is presented to implement the nonlinear state estimation. Finally, the proposed nonlinear state estimation methodology is applied to the state estimation for penicillin and industrial yeast fermentation processes. The simulation results show that the on-fine state estimation for fermentation process can be achieved by the proposed method with higher esti- mation accuracy and better stability.