Batch Process Modeling and Optimization through Wavelet Coefficient Regression

摘要：

A new regression and optimization method, wavelet coefficient regression and optimization (WCRO), is proposed to build an accurate statistical model that relates operation profiles with final product quality in a batch process and optimize operation profiles. In WCRO, important wavelet coefficients of operation profiles are selected as input variables of a statistical model, and then further dimensionality reduction is achieved through multivariate analysis. The indicator variable technique is integrated with WCRO to cope with the problem of unequal duration of each batch and to align batch trajectories. A case study of lysine production based on a semi-batch fermentation process demonstrates the superiority of the proposed method over the conventional multiway method.

关键词： Batch process Wavelet analysis Multivariate analysis Modeling Optimization

作者: Yosuke Mukai Kenichi Tasaka Koichi Fujiwara Manabu Kano Shinji Hasebe

作者单位: Department of Chemical Engineering,Kyoto University,Nishikyo-ku,Kyoto 615-8510,Japan

会议类型: 国际会议

会议名称: 第四届亚洲过程系统工程会议暨2007年中国国际系统工程年会(The 4th International Symposium on Design,Operation & Control of Chemical Processes)(PSE ASIA 2007)

会议地点: 西安

会议语种:英文

在线出版日期: 2007-08-15（万方平台首次上网日期，不代表论文的发表时间）