Soft-sensing of crucial biochemical variables in penicillin fermentation

Based on the ANN(Artificial Neural Network)-inversion soft-sensing method, the crucial biochemical variables which can not be directly measured in the penicillin fermentation process are soft-sensed in this paper. Firstly, the model of the “Assumed Inherent Sensor (AIS)” of the penicillin fermentation process is constructed. The inputs of the AIS are the directly immeasurable variables to be estimated, while the outputs are the directly measurable variables. In this paper, the improved Birol model is used to construct the model of the AIS. Secondly, the soft-sensor is constructed, which is just the inversion of the AIS. The result reveals that only the biomass concentration X and the substrate concentration S can be soft-sensed, but the penicillin concentration P can not be soft-sensed. Thirdly, the validity of the proposed ANN-inversion soft-sensor is verified by the simulation experiment. Finally, the soft-sensing problem of the penicillin concentration P is discussed. It can be seen that the proposed method is reasonable and reliable compared with other ANN soft-sensing methods.