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Dynamic optimization of complex distributed process systems

AuthorsBalsa-Canto, Eva ; Alonso, Antonio A. ; Banga, Julio R.
KeywordsDistributed parameter systems
Dynamic optimization
Second order parametric sensitivities
Proper orthogonal decomposition
Issue Date2005
PublisherInstitution of Chemical Engineers (Great Britain)
CitationChemical Engineering Research and Design 83(6): 724-729 (2005)
AbstractThe dynamicoptimization (DO) of complexdistributed parameter systems (DPSs), like e.g., reaction–diffusion processes, is a challenging task. Most of the existing numerical approaches imply a large computational effort, therefore precluding its application to demanding applications like real time DO or model predictive control. This work, based on the control vector parameterization (CVP) approach, describes two ways to enhance the efficiency of the resulting nonlinear programming (NLP) problem solution. On the one hand, the convergence properties of the NLP solver are enhanced through the use of exact gradients and projected Hessians (H.p). On the other hand, simulation efficiency is improved through the use of reduced order descriptions of the DPSs. The capabilities and possibilities of these two enhancements are illustrated with a number of complexdistributed case studies
Description6 páginas, 3 tablas, 4 figuras
Publisher version (URL)http://dx.doi.org/10.1205/cherd.04378
Appears in Collections:(IIM) Artículos
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