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Titre :
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Nonlinear model predictive control of high purity distillation columns for cryogenic air separation (2011)
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Auteurs :
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Zhongzhou Chen, Auteur ;
Michael A. Henson, Auteur ;
Paul Belanger, Auteur
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Type de document :
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Article : texte imprimé
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Dans :
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IEEE Transactions on control systems technology (Vol. 18 N° 4, Juillet 2010)
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Article en page(s) :
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pp. 811-821
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Note générale :
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Génie Aérospatial
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Langues :
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Anglais
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Index. décimale :
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629.1
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Tags :
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Nonlinear model predictive control (NMPC) Process Real time optimization Reduced-order modeling
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Résumé :
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High purity distillation columns are critical unit operations in cryogenic air separation plants that supply purified gases to a number of industries. We have developed a nonlinear model predictive control (NMPC) strategy based on the assumption of full-state feedback for a prototypical cryogenic distillation column to allow effective operation over a wide range of plant production rates. The controller design was based on a reduced-order compartmental model derived from detailed mass and energy balances by exploiting time-scale separations. Temporal discretization of the compartmental model produced a very large set of nonlinear differential and algebraic equations with advantageous sparsity properties, enabling online solution of the NMPC problem. The synergistic combination of several real-time implementation techniques were found to be essential for further reducing computation time and allowing reliable solution within the 2-min controller sampling interval. Closed-loop simulation studies demonstrated the performance advantages of NMPC compared to linear model predictive control technology currently used in the air separation industry.
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DEWEY :
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629.1
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ISSN :
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1063-6536
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En ligne :
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http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5288540
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