标题:The Hammerstein Predict Model of Control Valve Based on Least Square Support Vector Machine
作者:Huang, Ai-Qin; Wang, Yong
作者机构:[Huang, Ai-Qin; Wang, Yong] Shandong Univ, Sch Mech Engn, Jinan 250100, Peoples R China.
会议名称:4th International Conference on Mechanical Science and Technology (ICMSE 2014)
会议日期:JAN 02-04, 2014
来源:MECHANICAL SCIENCE AND ENGINEERING IV
出版年:2014
卷:472
页码:164-170
DOI:10.4028/www.scientific.net/AMM.472.164
关键词:Control valve; Hammerstein model; LS-SVM; Prediction
摘要:Control valve is a kind of essential terminal control component controlling the parameters of fluid such as flow and pressure in process-control. However it is a complex nonlinear, multi-input and single-output (MISO) system that is hard to model by traditional methodologies. To establish the pressure model of control valve, this paper presents a Hammerstein modeling method based on the least squares support vector machines (LS-SVM). The linear model parameters and the static nonlinearity of Hammerstein model can be obtained simultaneously by solving a set of linear equations followed by the singular value decomposition (SVD). As an example, a set of actual production data from a controlling system of chlorine in the salt chemistry industry were applied. The simulation results demonstrate that the obtained LS-SVM Hammerstein model can efficiently approximate the pressure of a control valve. Furthermore, the proposed LS-SVM Hammerstein model can be used in artificial intelligent control and the default diagnosis.
收录类别:CPCI-S;EI;SCOPUS
WOS核心被引频次:1
Scopus被引频次:1
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84892682653&doi=10.4028%2fwww.scientific.net%2fAMM.472.164&partnerID=40&md5=b7e7155edbee4a751eccf66c29df82e7
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