Bidirectional branch and bound for controlled variable selection. Part I: principles and minimum singular value criterion.

Show simple item record

dc.contributor.author Cao, Yi -
dc.contributor.author Kariwala, Vinay -
dc.date.accessioned 2012-10-03T23:01:39Z
dc.date.available 2012-10-03T23:01:39Z
dc.date.issued 2008-10-17T00:00:00Z -
dc.identifier.citation Yi Cao, Vinay Kariwala, Bidirectional branch and bound for controlled variable selection. Part I: Principles and minimum singular value criterion, Computers & Chemical Engineering, Volume 32, Issue 10, 17 October 2008, Pages 2306-2319 -
dc.identifier.issn 0098-1354 -
dc.identifier.uri http://dx.doi.org/10.1016/j.compchemeng.2007.11.011 -
dc.identifier.uri http://dspace.lib.cranfield.ac.uk/handle/1826/3072
dc.description.abstract The minimum singular value (MSV) rule is a useful tool for selecting controlled variables (CVs) from the available measurements. However, the application of the MSV rule to large-scale problems is difficult, as all feasible measurement subsets need to be evaluated to find the optimal solution. In this paper, a new and efficient branch and bound (BAB) method for selection of CVs using the MSV rule is proposed by posing the problem as a subset selection problem. In traditional BAB algorithms for subset selection problems, pruning is performed downwards (gradually decreasing subset size). In this work, the branch pruning is considered in both upward (gradually increasing subset size) and downward directions simultaneously so that the total number of subsets evaluated is reduced dramatically. Furthermore, a novel bidirectional branching strategy to dynamically branch solution trees for subset selection problems is also proposed, which maximizes the number of nodes associated with the branches to be pruned. Finally, by replacing time-consuming MSV calculations with novel determinant based conditions, the efficiency of the bidirectional BAB algorithm is increased further. Numerical examples show that with these new approaches, the CV selection problem can be solved incredibly fast. en_UK
dc.language.iso en_UK -
dc.publisher Elsevier Science B.V., Amsterdam. en_UK
dc.rights This is the author’s version of a work that was accepted for publication in Computers & Chemical Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers & Chemical Engineering, Volume 32, Issue 10, 17 October 2008, Pages 2306-2319 DOI:10.1016/j.compchemeng.2007.11.011
dc.subject Branch and bound en_UK
dc.subject Control structure design en_UK
dc.subject Controlled variables en_UK
dc.subject Combinatorial optimization en_UK
dc.subject Minimum singular value en_UK
dc.subject Self-optimizing control en_UK
dc.title Bidirectional branch and bound for controlled variable selection. Part I: principles and minimum singular value criterion. en_UK
dc.type Article -


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search CERES


Browse

My Account

Statistics