基于EM算法的青霉素发酵过程多阶段融合建模

doi:10.3969/j.issn.0438-1157.2014.12.039

化工学报 ›› 2014, Vol. 65 ›› Issue (12): 4935-4941.DOI: 10.3969/j.issn.0438-1157.2014.12.039

基于EM算法的青霉素发酵过程多阶段融合建模

熊伟丽^1,2, 姚乐², 徐保国^1,2

1. 江南大学轻工过程先进控制教育部重点实验室, 江苏无锡 214122;
2. 江南大学物联网工程学院自动化研究所, 江苏无锡 214122

收稿日期:2014-09-19 修回日期:2014-09-23 出版日期:2014-12-05 发布日期:2014-12-05
通讯作者: 熊伟丽
基金资助:
国家自然科学基金项目(21206053,21276111);江苏高校优势学科建设工程资助项目(PAPD).

Multi-stage fusion modeling for penicillin fermentation process based on EM algorithm

XIONG Weili^1,2, YAO Le², XU Baoguo^1,2

1. Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi 214122, Jiangsu, China;
2. School of Internet of Things Engineering, Institute of Automation, Jiangnan University, Wuxi 214122, Jiangsu, China

Received:2014-09-19 Revised:2014-09-23 Online:2014-12-05 Published:2014-12-05
Supported by:
supported by the National Natural Science Foundation of China (21206053, 21276111) and by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).

摘要/Abstract

摘要： 青霉素发酵过程具有明显的阶段特征,该特征从一些关键操作变量信息中能够得到反映.本文从反应过程的多个操作变量中,选取关键过程变量——冷水流加速率作为调度变量,并采用模糊C均值聚类算法对其进行分类,各聚类中心作为青霉素发酵过程的主要工况点;基于EM算法围绕不同工况点建立局部子模型,最后根据采样数据阶段特征的后验分布将各子模型融合.基于此方法采用Pensim仿真平台数据,能够辨识数据的阶段特征,并建立青霉素发酵过程的融合模型.仿真结果表明该模型具有较高的拟合精度,能对该发酵过程的主导变量进行比较精确的预测.

关键词: EM算法, 模糊C均值聚类算法, 青霉素发酵过程, 融合建模

Abstract: Penicillin fermentation process has the feature of the distinct phases, which can be seen from some key operating variables. In this paper, the key process variable, namely, the cold water flow rate was taken as the scheduling variable, which was then classified by the fuzzy C-means clustering algorithm. The cluster centers were considered as the main operating points of the penicillin fermentation process. Local models were constructed around each operating point based on EM algorithm. Thereafter, sub-models were combined togethter according to the posterior distribution of the scheduling variable. The feasiblity and effectiveness of the proposed method was illustrated through the Pensim simulation platform.

Key words: EM algorithm, fuzzy C-means clustering algorithm, penicillin fermentation process, fusion modeling

中图分类号:

TP183

熊伟丽, 姚乐, 徐保国. 基于EM算法的青霉素发酵过程多阶段融合建模[J]. 化工学报, 2014, 65(12): 4935-4941.

XIONG Weili, YAO Le, XU Baoguo. Multi-stage fusion modeling for penicillin fermentation process based on EM algorithm[J]. CIESC Journal, 2014, 65(12): 4935-4941.

参考文献 24

[1]	Sun Qi. Analysis of characteristics of penicillin fermentation process and its control method [J]. Technology Innovation and Application, 2012, 5(12): 29-30
[2]	Gao Xuejin, Wang Pu, Sun Chongzheng, Yi Jianqiang, Zhang Yating, Zhang Huiqing. Research and application of method on modeling by dividing phases for fermentation process [J]. Journal of System Simulation, 2007, 19(11): 2574-2577
[3]	Zhao Juanping, Chen Jian, Jiang Changhong. Modeling of the penicillin fermentation process [J]. Computer Simulation, 2008, 25(2): 80-82
[4]	Wang Xianfang, Chen Jindong, Liu Chunbo, Pan Feng. Hybrid modeling of penicillin fermentation process based on least square support vector machine [J]. Chemical Engineering Research and Design, 2010, 88(4): 415-420
[5]	Liu Yi, Wang Haiqing. Modeling a penicillin fed-batch fermentation using least squares support vector machines [J]. Chinese Journal of Biotechnology, 2006, 22(1): 144-149
[6]	Liu Guohai, Zhou Dawei, Xu Haixia, Mei Congli. Model optimization of SVM for a fermentation soft sensor [J]. Expert Systems with Applications, 2010, 37(4): 2708-2713
[7]	Fernando D S, Adriana N A. Biomass estimation in batch biotechnological processes by bayesian Guassian process regression [J]. Computers & Chemical Engineering, 2008, 32(12): 3264-3273
[8]	Zhao Zhonggai, Huang Biao, Liu Fei. Parameter estimation in batch process using EM algorithm with particle filter [J]. Computers & Chemical Engineering, 2013, 57: 159-172
[9]	Jin Xing, Wang Siyun, Huang Biao, Forbes Fraser. Multiple model based LPV soft sensor development with irregular/missing process output measurement [J]. Control Engineering Practice, 2012, 20(2): 165-172
[10]	Chen Lei, Liu Fei. Recursive parameter identification for fermentation processes with the multiple model technique [J]. Applied Mathematical Modeling, 2012, 36(5): 2275-2285
[11]	Chen Lei, Aditya Tulsyan, Huang Biao, Liu Fei. Multiple model approach to non-linear system identification with uncertain scheduling variables using EM algorithm [J]. Journal of Process Control, 2013, 23(10): 1480-1496
[12]	Zhu Y, Xu Z. A method of LPV model identification for control//17th IFAC World Congress[C]. Soul, Korea, 2008:5018-5023
[13]	Sun W, Meng Y, Palazoglu A, Zhao J, Zhang H, Zhang J.A method for multiphase batch process monitoring based on auto phase identification [J]. Journal of Process Control, 2011, 21(4): 627-638
[14]	Yao Yuan, Gao Furong. Phase and transition based on batch process modeling and online monitoring [J]. Journal of Process Control, 2009, 19(5): 816-826
[15]	Wu Jiaxin, Zhang Guodong, Liu Xiaojie, Qi Peng, Zheng Yinghua, He Jihong, Song Min, Ge Xinmei, Wang Huali, Cao Qin. Application of cluster analysis on flavomycin fermentation [J]. Microbiology China, 2012, 39(6): 865-871
[16]	Gong Gaiyun. Study of FCM algorithm on parameters and its applications[D]. Xi'an: Xi'an University of Electronic Science and Technology, 2004
[17]	Dempster A P, Laird N M, Rubin D B. Maximum likelihood from incomplete data via the EM algorithm [J]. J. R Stat. Soc. Series B, 1977, 39:1-38
[18]	Jin X, Huang B, Shook D S. Multiple model LPV approach to nonlinear process identification with EM algorithm [J]. Journal of Process Control, 2011, 21(1): 182-193
[19]	Jin X, Huang B. Robust identification of piecewise/ switching autoregressive exogenous process [J]. AIChE Journal, 2010, 56(7): 1829-1844
[20]	Liu Yi, Wang Haiqing. Pensim simulator and its application in penicillin fermentation process [J]. Journal of System Simulation, 2006, 18(12): 3524-3527
[21]	He Xiaoran, Chen Chen, Kim Kwang Sok, Xiong Zhihua. Model simulation of fed-batch penicillin fermentation and optimization of substrate feed rate [J]. Chinese Journal of Chemical Engineering, 2012, 63(9): 2831-2835
[22]	Bajpai R K, Reuss M. A mechanistic model for penicillin production [J]. J. Chem. Tech. Biotechnol., 1980, 30:330-334
[23]	Birol G, Undey C, Cinar A. A modular simulation package for fed-batch fermentation: penicillin production [J]. Computers and Chemical Engineering, 2002, 26(11): 1553-1565
[24]	Liu Yi, Wang Haiqing. Modeling of the penicillin fermentation process via LSSVM based on Pensim simulator [J]. Chemical Reaction Engineering and Technology, 2006, 22(3): 252-258
[23]	Birol G, Undey C, Cinar A. A modular simulation package for fed-batch fermentation: penicillin production [J]. Computers and Chemical Engineering, 2002, 26(11): 1553-1565
[24]	Liu Yi, Wang Haiqing. Modeling of the penicillin fermentation process via LSSVM based on Pensim simulator [J]. Chemical Reaction Engineering and Technology, 2006, 22(3): 252-258

基于EM算法的青霉素发酵过程多阶段融合建模

Multi-stage fusion modeling for penicillin fermentation process based on EM algorithm

PDF (PC)

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献 24

相关文章 6

编辑推荐

Metrics

本文评价

[1]	王幼琴, 赵忠盖, 刘飞. 缺失数据下基于EM算法的非线性过程建模[J]. 化工学报, 2016, 67(3): 931-939.
[2]	王亚君, 孙福明. 基于多动态核聚类的间歇过程在线监控[J]. 化工学报, 2014, 65(12): 4905-4913.
[3]	丰娟1，唐勇波2，3，彭涛3. 基于KTA-LSSVM的青霉素发酵过程预测建模[J]. 化工进展, 2014, 33(09): 2438-2443.
[4]	李嘉雯, 杜文莉, 李进龙, 钱锋. 基于改进模糊C均值聚类算法的乙烯裂解原料识别[J]. 化工学报, 2013, 64(12): 4366-4372.
[5]	刘毅, 王海清, 李平. 关键核网络及其在发酵过程在线建模中的应用 [J]. 化工学报, 2008, 59(5): 1194-1199.
[6]	刘世成, 高彦臣, 王海清, 李平. 特征空间递归更新的ICA算法及发酵过程监测应用 [J]. 化工学报, 2008, 59(11): 2830-2836.