Strategies for Optimizing Feed Rate of Fed-Batch Yeast Fermentation by Fuzzy-Neural Network  

作　　者：苗志奇 元英进 

出　　处：《Chinese Journal of Chemical Engineering》1998年第4期62-69,共8页中国化学工程学报（英文版）

基　　金：Supported by the National Natural Science Foundation of China,No.29476248 and Trans-Century Training Program Foundation for the Talents by the State Education Commission.

摘　　要：In this paper,a novel fuzzy neural network model,in which an adjustable fuzzy sub-space was designed by uniform design,has been established and used in fed-batch yeast fermentationas an example.A brand-new optimization sub-network with special structure has been built andgenetic algorithm,guaranteeing the optimization in overall space,is introduced for the feed rateoptimization.On the basis of the model network,the optimal substrate concentration and theoptimal amount of fed-batch at different periods have been studied,aided with the optimizationnetwork and the genetic algorithm separately.The above results can be used as a basis for theestablishment of a fuzzy neural network controller.In this paper, a novel fuzzy neural network model, in which an adjustable fuzzy sub-space was designed by uniform design, has been established and used in fed-batch yeast fermentation as an example. A brand-new optimization sub-network with special structure has been built and genetic algorithm, guaranteeing the optimization in overall space, is introduced for the feed rate optimization. On the basis of the model network, the optimal substrate concentration and the optimal amount of fed-batch at different periods have been studied, aided with the optimization network and the genetic algorithm separately. The above results can. be used as a basis for the establishment of a fuzzy neural network controller.

关 键 词：FUZZY NEURAL network optimization FED-BATCH FERMENTATION the GENETIC algorithm 

分 类 号：TQ018[化学工程]