dc.contributor.authorKariwala, Vinay
dc.contributor.authorCao, Yi
dc.date.accessioned2013-10-23T08:49:17Z
dc.date.available2013-10-23T08:49:17Z
dc.date.copyright2012en_US
dc.date.issued2012
dc.identifier.citationKariwala, V., & Cao, Y. (2012). Multiobjective control structure design: A branch and bound approach. Industrial & engineering chemistry research, 51(17), 6064-6070.en_US
dc.identifier.issn0888-5885en_US
dc.identifier.urihttp://hdl.handle.net/10220/16754
dc.description.abstractControl structure design traditionally involves two steps of selections, namely the selection of controlled and manipulated variables and the selection of pairings interconnecting these variables. The available criteria for both selections require enumeration of every alternative. Hence, an exhaustive search can be computationally forbidding for large-scale processes. On the other hand, owing to the computational complexity, variables and pairings are often selected sequentially, which may result in suboptimal control structures. In this paper, an efficient branch and bound (BAB) method is proposed to select the variables and pairings together in a multiobjective optimization framework. As an illustration of the proposed multiobjective BAB framework, the minimum singular value rule and the μ-interaction measure are used as the criteria for selection of controlled variables and pairings, respectively. Numerical tests using randomly generated matrices and the large-scale case study of hydrodealkylation of toluene (HDA) process show that the BAB method is able to reduce the solution time by several orders of magnitude in comparison with exhaustive search.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesIndustrial & engineering chemistry researchen_US
dc.subjectDRNTU::Engineering::Chemical engineering
dc.titleMultiobjective control structure design: A branch and bound approachen_US
dc.typeJournal Article
dc.contributor.schoolSchool of Chemical and Biomedical Engineeringen_US
dc.identifier.doihttp://dx.doi.org/10.1021/ie201510c


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