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dc.contributor.authorWang, L.
dc.contributor.authorLin, Qun
dc.contributor.authorLoxton, Ryan
dc.contributor.authorTeo, Kok Lay
dc.contributor.authorCheng, G.
dc.date.accessioned2017-01-30T11:36:57Z
dc.date.available2017-01-30T11:36:57Z
dc.date.created2015-07-14T20:00:44Z
dc.date.issued2015
dc.identifier.citationWang, L. and Lin, Q. and Loxton, R. and Teo, K.L. and Cheng, G. 2015. Optimal 1,3-propanediol production: Exploring the trade-off between process yield and feeding rate variation. Journal of Process Control. 32: pp. 1-9.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/13423
dc.identifier.doi10.1016/j.jprocont.2015.04.011
dc.description.abstract

This paper proposes a new optimal control model for the production of 1,3-propanediol (1,3-PD) viamicrobial fed-batch fermentation. The proposed model is governed by a nonlinear multi stage dynamic system with two modes: feeding mode, in which glycerol and alkali substrates are added continuously to the fermentor; and batch mode, in which no substrates are added to the fermentor. The non-standard objective function incorporates both the final 1,3-PD yield and the cost of changing the input feeding rate, which is the control variable for the fed-batch fermentation process. Continuous state inequality constraints are imposed to ensure that the concentrations of biomass, glycerol, and reaction products lie within specified limits. Using the constraint transcription method, we approximate the continuous state inequality constraints by a conventional inequality constraint to yield an approximate parameter optimization problem. We then develop a combined particle swarm and gradient-based optimization algorithm to solve this approximate problem. The paper concludes with simulation results.

dc.publisherElsevier Ltd.
dc.subjectMultistage dynamic systems
dc.subjectFed-batch fermentation
dc.subjectTotal variationa
dc.subjectNonlinear systems
dc.subjectOptimal control
dc.titleOptimal 1,3-propanediol production: Exploring the trade-off between process yield and feeding rate variation
dc.typeJournal Article
dcterms.source.volume32
dcterms.source.startPage1
dcterms.source.endPage9
dcterms.source.issn0959-1524
dcterms.source.titleJournal of Process Control
curtin.departmentDepartment of Mathematics and Statistics
curtin.accessStatusOpen access


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