基于SVM-IGA的补料分批发酵过程优化控制

Optimization Control of Material Makeup Ferment Process in Batches Based on SVM-IGA

针对非线性时变的发酵过程,建立了用于产物浓度预估的支持向量机(SVM)模型。在此模型基础上,利用免疫遗传算法(IGA)实现对发酵过程补料优化控制参数的寻优;实验结果表明,该方法可行,且能提高产物的产量;所提出的这种方法是对解决补料分批发酵过程优化问题的一个新尝试。

In accordance with the features of non-linear and time varying for ferment process, a support vector machines （SVM） model is established for estimating the concentration of product. Based on this SVM model, immune genetic algorithm （IGA） is applied to realize parameter optimization of material makeup ferment process control. The experimental results show that this optimization method is reliable and it can improve the output of product. The method presented provides a new approach to deal with the problems of optimization control of material makeup ferment process in batches.