Multivariate feed back control: an application in a productive process
The main purpose of this research is to implement a multivariate feedback adjustment proportional to the last deviation from the target, in the set of variables wandering around the target. To apply the controller equation it will be necessary to study the exponentially weighted moving average ( EWM...
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Veröffentlicht in: | Computers & industrial engineering 2004-07, Vol.46 (4), p.837-850 |
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creator | Mendonça Souza, Adriano Wayne Samohyl, Robert Malavé, César O |
description | The main purpose of this research is to implement a multivariate feedback adjustment proportional to the last deviation from the target, in the set of variables wandering around the target. To apply the controller equation it will be necessary to study the exponentially weighted moving average (
EWMA) statistic, in order to determine the behavior of the target disturbances. To determine the forecast values of the variables we will use Seemingly Unrelated Regression (
SUR), which is necessary since there is a relationship between the variables and between the errors. In this manner, multivariate feedback adjustment can be reached based on scientific grounds. |
doi_str_mv | 10.1016/j.cie.2004.05.013 |
format | Article |
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EWMA) statistic, in order to determine the behavior of the target disturbances. To determine the forecast values of the variables we will use Seemingly Unrelated Regression (
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EWMA) statistic, in order to determine the behavior of the target disturbances. To determine the forecast values of the variables we will use Seemingly Unrelated Regression (
SUR), which is necessary since there is a relationship between the variables and between the errors. In this manner, multivariate feedback adjustment can be reached based on scientific grounds.</description><subject>Engineering process control</subject><subject>Monitoring</subject><subject>Multivariate analysis</subject><subject>Multivariate feedback control</subject><subject>Process planning</subject><subject>Proportional feedback</subject><subject>Regression analysis</subject><subject>Seemingly unrelated regression</subject><subject>Statistical process control</subject><subject>Studies</subject><issn>0360-8352</issn><issn>1879-0550</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><recordid>eNp9kLtOwzAUhi0EEuXyAGwRA1vCsV3HNkyoooBUxAKz5TrHkkOaFDupxNvjqkwMTD6Wvu9cfkKuKFQUaH3bVi5gxQDmFYgKKD8iM6qkLkEIOCYz4DWUigt2Ss5SaiGDQtMZWb5O3Rh2NgY7YuERm2Jt3Wfhhn6MQ3dX2L6w220XnB3D0Bchf4ttHJrJZQ33pcOULsiJt13Cy9_3nHwsH98Xz-Xq7ell8bAqHRd8LFXTMOkFo6B1zZVHqdkaJeco115xTmsu1dxxXQuN3gOztXIAXDvPlEDLz8nNoW-e-zVhGs0mJIddZ3scpmSY5qquKc3g9R-wHabY590Mo1zOpZR7iB4gF4eUInqzjWFj47ehYPaxmtbkWM0-VgPC5Fizc39wMJ-5CxhNykjvsAkR3WiaIfxj_wBhnX55</recordid><startdate>20040701</startdate><enddate>20040701</enddate><creator>Mendonça Souza, Adriano</creator><creator>Wayne Samohyl, Robert</creator><creator>Malavé, César O</creator><general>Elsevier Ltd</general><general>Pergamon Press Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20040701</creationdate><title>Multivariate feed back control: an application in a productive process</title><author>Mendonça Souza, Adriano ; Wayne Samohyl, Robert ; Malavé, César O</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c353t-8dd27f521099638fe792be733e7bf833163784c39659eff02a68c0039cf285ea3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Engineering process control</topic><topic>Monitoring</topic><topic>Multivariate analysis</topic><topic>Multivariate feedback control</topic><topic>Process planning</topic><topic>Proportional feedback</topic><topic>Regression analysis</topic><topic>Seemingly unrelated regression</topic><topic>Statistical process control</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mendonça Souza, Adriano</creatorcontrib><creatorcontrib>Wayne Samohyl, Robert</creatorcontrib><creatorcontrib>Malavé, César O</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Computers & industrial engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mendonça Souza, Adriano</au><au>Wayne Samohyl, Robert</au><au>Malavé, César O</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Multivariate feed back control: an application in a productive process</atitle><jtitle>Computers & industrial engineering</jtitle><date>2004-07-01</date><risdate>2004</risdate><volume>46</volume><issue>4</issue><spage>837</spage><epage>850</epage><pages>837-850</pages><issn>0360-8352</issn><eissn>1879-0550</eissn><coden>CINDDL</coden><abstract>The main purpose of this research is to implement a multivariate feedback adjustment proportional to the last deviation from the target, in the set of variables wandering around the target. To apply the controller equation it will be necessary to study the exponentially weighted moving average (
EWMA) statistic, in order to determine the behavior of the target disturbances. To determine the forecast values of the variables we will use Seemingly Unrelated Regression (
SUR), which is necessary since there is a relationship between the variables and between the errors. In this manner, multivariate feedback adjustment can be reached based on scientific grounds.</abstract><cop>New York</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.cie.2004.05.013</doi><tpages>14</tpages></addata></record> |
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subjects | Engineering process control Monitoring Multivariate analysis Multivariate feedback control Process planning Proportional feedback Regression analysis Seemingly unrelated regression Statistical process control Studies |
title | Multivariate feed back control: an application in a productive process |
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