Soft Sensor Model Derived from Wiener Model Structure: Modeling and Identification
源于Wiener非线性模型的软仪表系统建模及其辨识(英文)作者机构：Research Institute of Automation China University of Petroleum
出 版 物：《Chinese Journal of Chemical Engineering》 (中国化学工程学报（英文版）)
年 卷 期：2014年第22卷第5期
页 面：538-548页
核心收录：
基 金：Supported by the National Natural Science Foundation of China(61104218,21006127) the National Basic Research Program of China(2012CB720500) the Science Foundation of China University of Petroleum(YJRC-2013-12)
主 题：soft sensor Wiener model modeling alternate identification
摘 要：The processes of building dynamic and static relationships between secondary and primary variables are usually integrated in most of nonlinear dynamic soft sensor models. However, such integration limits the estimation accuracy of soft sensor models. Wiener model effectively describes dynamic and static characteristics of a system with the structure of dynamic and static submodels in cascade. We propose a soft sensor model derived from Wiener model structure, which is an extension of Wiener model. Dynamic and static relationships between secondary and primary variables are built respectively to describe the dynamic and static characteristics of system. The feasibility of this model is verified. Then the expression of discrete model is derived for soft sensor system. Conjugate gradient algorithm is applied to identify the dynamic and static model parameters alternately. Corresponding update method for soft sensor system is also given. Case studies confirm the effectiveness of the proposed model, alternate identification algorithm, and update method.
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