Penicillin fermentation process has the feature of the distinct phases

which can be seen from some key operating variables. In this paper

the key process variable

namely

the cold water flow rate was taken as the scheduling variable

which was then classified by the fuzzy C-means clustering algorithm. The cluster centers were considered as the main operating points of the penicillin fermentation process. Local models were constructed around each operating point based on EM algorithm. Thereafter

sub-models were combined togethter according to the posterior distribution of the scheduling variable. The feasiblity and effectiveness of the proposed method was illustrated through the Pensim simulation platform.