Progress and Challenges in Control of Chemical Processes

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dc.contributor.authorLee, JayHyungko
dc.contributor.authorLee, Jong Minko
dc.date.accessioned2014-09-02-
dc.date.available2014-09-02-
dc.date.created2014-04-10-
dc.date.created2014-04-10-
dc.date.created2014-04-10-
dc.date.issued2014-06-
dc.identifier.citationANNUAL REVIEW OF CHEMICAL AND BIOMOLECULAR ENGINEERING, VOL 5, v.5, pp.383 - 404-
dc.identifier.issn1947-5438-
dc.identifier.urihttp://hdl.handle.net/10203/189691-
dc.description.abstractThis review covers key developments and trends in chemical process control during the past two decades. Control methodologies and related supporting technologies are covered, and recent trends in applications are also examined. After the widespread adoption of model-based techniques by industry, control interest has begun to move beyond the traditional realm of readily measured variables to include chemical compositions and particle features. However, the shift is being slowed by the shortage of accurate, reliable, and inexpensive sensing devices. Although the past two decades saw no new major theoretical or methodological advances, several important incremental improvements and extensions have been made to help the ripening of the technologies developed in the preceding two decades. Control is regaining its importance owing to society's renewed focus on energy and the maturation of various emerging technologies, but a community-wide consensus on what general problems should be solved is lacking.-
dc.languageEnglish-
dc.publisherANNUAL REVIEWS-
dc.subjectMODEL-PREDICTIVE CONTROL-
dc.subjectNONLINEAR STATE ESTIMATION-
dc.subjectREAL-TIME OPTIMIZATION-
dc.subjectTO-RUN CONTROL-
dc.subjectSOFT-SENSOR-
dc.subjectPOLYMERIZATION PROCESS-
dc.subjectDYNAMIC OPTIMIZATION-
dc.subjectBATCH PROCESSES-
dc.subjectSYSTEMS-
dc.subjectSTABILITY-
dc.titleProgress and Challenges in Control of Chemical Processes-
dc.typeArticle-
dc.identifier.wosid000340198000019-
dc.identifier.scopusid2-s2.0-84902532475-
dc.type.rimsART-
dc.citation.volume5-
dc.citation.beginningpage383-
dc.citation.endingpage404-
dc.citation.publicationnameANNUAL REVIEW OF CHEMICAL AND BIOMOLECULAR ENGINEERING, VOL 5-
dc.identifier.doi10.1146/annurev-chembioeng-060713-035908-
dc.contributor.localauthorLee, JayHyung-
dc.contributor.nonIdAuthorLee, Jong Min-
dc.type.journalArticleReview; Book Chapter-
dc.subject.keywordAuthormodel-based control-
dc.subject.keywordAuthoron-line optimization-
dc.subject.keywordAuthorstate estimation-
dc.subject.keywordAuthorsensors and instrumentation-
dc.subject.keywordAuthoremerging applications-
dc.subject.keywordAuthormodel-based control-
dc.subject.keywordAuthoron-line optimization-
dc.subject.keywordAuthorstate estimation-
dc.subject.keywordAuthorsensors and instrumentation-
dc.subject.keywordAuthoremerging applications-
dc.subject.keywordPlusMODEL-PREDICTIVE CONTROL-
dc.subject.keywordPlusNONLINEAR STATE ESTIMATION-
dc.subject.keywordPlusMOVING-HORIZON ESTIMATION-
dc.subject.keywordPlusREAL-TIME OPTIMIZATION-
dc.subject.keywordPlusTO-RUN CONTROL-
dc.subject.keywordPlusSOFT-SENSOR-
dc.subject.keywordPlusPOLYMERIZATION PROCESS-
dc.subject.keywordPlusDYNAMIC OPTIMIZATION-
dc.subject.keywordPlusBATCH PROCESSES-
dc.subject.keywordPlusSYSTEMS-
dc.subject.keywordPlusMODEL-PREDICTIVE CONTROL-
dc.subject.keywordPlusNONLINEAR STATE ESTIMATION-
dc.subject.keywordPlusMOVING-HORIZON ESTIMATION-
dc.subject.keywordPlusREAL-TIME OPTIMIZATION-
dc.subject.keywordPlusTO-RUN CONTROL-
dc.subject.keywordPlusSOFT-SENSOR-
dc.subject.keywordPlusPOLYMERIZATION PROCESS-
dc.subject.keywordPlusDYNAMIC OPTIMIZATION-
dc.subject.keywordPlusBATCH PROCESSES-
dc.subject.keywordPlusSYSTEMS-
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