青霉素发酵过程中的混合建模

由于微生物发酵过程机理的复杂性和高度非线性,建立发酵过程的精确模型具有一定难度。传统的动力学模型预测虽然会与实际输出有一定偏差,但它在某种程度上反映了过程机理;神经网络建模方法属于"黑箱"方法,建模过程中没有用到任何先验知识,有一定的预测效果;因此单一的建模方法往往会不具备其他建模方法的优势。本文以传统的发酵动力学模型为基础,结合RBF神经网络进行混合建模的"灰箱"建模方法是一种比较好的建模思路,可以取得较满意的软测量效果。

Hybrid modeling for penicillin fermentation process

Due to the complexity and high non-linearity of microbial fermentation process, it is difficult to model the process of fermentation precisely.Although there is a predictive error between traditional mechanistic model and testing result, it reflects the process of mechanism.Neural network modeling method is classified as “black box” method: the process of modeling uses no priori knowledge, and gets a good result, so single soft sensor modeling method can not have the advantages of the others.This paper uses RBF neural network and mechanistic model to model and constitutes a “cinder box” hybrid model, which is a good modeling method.