【作者】 胡益； 马贺贺； 侍洪波；

【Author】 Hu Yi,Ma Hehe. Shi hongbo Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education,East China University of Science and Technology,Shanghai 200237,China

【机构】 华东理工大学化工过程先进控制和优化技术教育部重点实验室；

【摘要】 针对间歇过程存在的非线性、动态性和多阶段特性,将局部建模策略融入到核偏最小二乘(KPLS)方法中,提出了一种新的间歇过程在线建模和在线监控方法。经过改进的局部建模方法不仅利用了间歇过程当前时间片包含的信息,而且考虑了与新样本相关的近邻时间片的信息,从而使建立的局部模型能准确地反映过程的变化,有效地克服了过程的动态问题和多阶段问题。同时,KPLS算法在处理非线性问题时能够很好地建立起输入变量与输出变量之间的非线性关系,充分提取非线性系统的特征。通过一个实际的半导体制造过程的实验研究,表明提出的新方法可以更有效地处理间歇过程数据信息。更多还原

【Abstract】 To handle the problems of nonlinearity, dynamic and multiphase in batch processes,a novel online modeling and monitoring method based on local model and kernel partial least squares (KPLS) is proposed. The improved local modeling method not only utilizes the information of the current time slice. but also incorporates the information of the nearby time slices.The local model can reflect the changes of operating process, so it can be used to monitor processes with time-varying behavior and operating phase change.Besides,KPLS is employed to model the nonlinear information of the process. A case study of the semiconductor process illustrated that the proposed approach can effectively monitor the batch process.更多还原