Joint Estimation in Batch Culture by Using Unscented Kalman Filter

다국어 초록 (Multilingual Abstract)

The disturbances caused by uncertain factors are inevitable in microbial fermentation. In this paper, we study the joint estimation problem for state and parameter in the bio-dissimulation process of glycerol to 1,3-PD in batch culture. Based on the nonlinear stochastic dynamic system model, we establish the corresponding iteration equations of Joint Unscented Kalman Filter (UKF) by referring to the Extended Kalman Filter (EKF), which is generally applied in microbial fermentation. Through numerical computation, both the state estimations and the uncertain model parameter estimations are obtained.
Furthermore, the results of different parameter identification methods are compared. The results show that Joint UKF is more feasible for the process of controlling the glycerol fermentation.

다국어 초록 (Multilingual Abstract)

The disturbances caused by uncertain factors are inevitable in microbial fermentation. In this paper, we study the joint estimation problem for state and parameter in the bio-dissimulation process of glycerol to 1,3-PD in batch culture. Based on the nonlinear stochastic dynamic system model, we establish the corresponding iteration equations of Joint Unscented Kalman Filter (UKF) by referring to the Extended Kalman Filter (EKF), which is generally applied in microbial fermentation. Through numerical computation, both the state estimations and the uncertain model parameter estimations are obtained.
Furthermore, the results of different parameter identification methods are compared. The results show that Joint UKF is more feasible for the process of controlling the glycerol fermentation.

참고문헌 (Reference)

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