摘要
丁二酸是一种重要的化工原料,应用领域广泛。现阶段有关丁二酸发酵的研究重点集中在菌种选育和发酵工艺改良,而丁二酸发酵过程的模型化研究可以为工艺放大提供必要的基础数据。在对文献中已有的丁二酸发酵过程动力学模型做进一步探讨的基础上,对模型的结构做适当调整,并将遗传算法应用于该动力学模型的参数优化。结果表明,遗传算法能进一步提高模型计算值与丁二酸发酵实验测量值的吻合程度,可以有效地解决发酵动力学模型这类复杂的非线性函数的参数优化问题,优于单纯形法。遗传算法进行参数优化得到的动力学模型能较好地模拟丁二酸发酵过程。
As an important material widely used in many areas, succinic acid plays a significant role in chemical industries. The main research of the fermentation process of succinic acid focuses on the breeding of succinic acid and the improvement of the fermentation technology at the present stage. Whereas, the study of the modeling for the fermentation process of succinic acid can provide basic data for the industrialization of the fermentation technology. Based on the further discussion of kinetic models for the fermentation process of succinic acid proposed by other researchers, the structure of the model was modified properly and genetic algorithm was applied in the optimization of kinetic parameters. The resuhs indicates that the consistence of calculated and experimental data is improved. Genetic algorithm can be used to solve the optimization of kinetic parameters of the complex nonlinear problem effectively. With the optimized model parameters, the kinetic models can provide reasonable simulation of the fermentation process of suecinic acid.
出处
《计算机仿真》
CSCD
北大核心
2010年第3期193-197,共5页
Computer Simulation
关键词
丁二酸发酵过程
动力学模型
遗传算法
参数优化
Fermentation process of succinic acid
Kinetic models
Genetic algorithm
Optimization of parameters
