摘要
丁二酸是一种重要的化工原料,对丁二酸发酵过程进行模型化研究可以为工艺放大提供必要的基础数据。根据丁二酸发酵过程的实验数据,在已有的丁二酸发酵动力学模型的基础上,采用粒子群优化算法进行模型参数优化研究,求得最优参数并利用其进行过程仿真。结果表明优化后的模型能够更好地模拟丁二酸分批发酵过程。和采用遗传算法进行的研究结果相比,粒子群算法提高了模型计算值与实验测量值的拟合程度,且算法简单,易于实现。
Succinic acid is an important chemical material. Building the model for the fermentation process of succinic acid can provide basic data for the industrialization of the fermentation technology. Particle swarm optimization （PS0） method was used to optimize the parameter of the kinetic model for the succinic acid fermentation based on the experimental data, the optimal parameters was found and the simulation of the process was made. The result shows that the model can simulate the process of succinic acid fermentation better. Comparing with GA method, the model which optimized by PSO improves the coincidence of calculated data and experimental data, and PSO method is simple and easy to realize.
出处
《化工自动化及仪表》
CAS
北大核心
2010年第3期10-13,共4页
Control and Instruments in Chemical Industry
基金
国家自然科学基金资助项目(20606017)
关键词
丁二酸发酵
动力学模型
参数优化
粒子群算法
succinic acid fermentation
kinetic model
parameter optimization
particle swarm optimization
