Treatment methods of abnormality in FIR Model Identification

摘要：

This article mainly focuses on two treatment methods in FIR model identification for the abnormality in measured data set. One is called linear interpolation method(LIM), whose essence is to rebuild the data set according to linear interpolation after indicating the abnormal data. The other is the method of identification based on segments of data(ISDM). The idea is to remove the abnormal data and divide the original data set into two or more inconsecutive data sets, then perform model identification using those data sets respectively, finally merge the results with different weighted means. The guidelines of the proposed methods are enumerated. The two methods are illustrated with FIR model identification, and simulations with the Shell heavy oil fractionator model verify the feasibility and effectiveness.

作者: Yan Ping Hong Xiong Xiong He Tao Zou Dong Ya Zhao

作者单位: Department of Information Engineering, ZheJiang University of Technology, HangZhou 310023, ZheJiang, Department of Mechanical and Electronic Engineering,China University of Petroleum, DongYing 257061,

会议类型: 国际会议

会议名称: 2011 International Symposium on Advanced Control of Industrial Processes(2011工业过程先进控制技术国际研讨会)

会议地点: 杭州

会议语种:英文

页码: 482-485

在线出版日期: 2011-05-01（万方平台首次上网日期，不代表论文的发表时间）