文章基本信息

标题：Variability Reduction Estimation for SISO Systems through Unmeasured Disturbance Estimation
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作者：Maria A.F. Lima ; Jorge O. Trierweiler ; Marcelo Farenzena 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2016
卷号：49
期号：7
页码：377-382
DOI：10.1016/j.ifacol.2016.07.366
语种：English
出版社：Elsevier
摘要：The variability within a process can be seen as a limiting factor for its efficiency. Because this, the present paper provides a simple, fast and non-intrusive methodology, able to translate the part in total variability that can be changed through controller adjustment. These types of analyses are usually intrusive; however, this work presents an alternative to obtaining such information from non-intrusive manner, thus eliminating a need for system perturbation. It is proposed to estimate the variability reduction through a sequential method that uses unmeasured disturbance estimation and a representative model of the actual process. The method’s quality was tested by analyzing the sensitivity of methodology against several initial conditions, since the procedure requires an optimization step. The case studies that involved pure time delay have showed high sensitivity to the initial condition, but even in this case the potential for variability reduction was correctly estimated.
关键词：Performance MonitoringVariabilityLoop MaintenanceUnmeasured DisturbanceVariance