Abstract
In many applications, e.g., in chemical process control, the purpose of control is to achieve an optimal performance of the controlled system despite the presence of significant uncertainties about its behavior and of external disturbances. Tracking of set points is often required for lower-level control loops, but at the system level in most cases, this is not the primary concern and may even be counterproductive. In this entry, the use of dynamic online optimization on a moving finite horizon to realize optimal system performance is discussed. By real-time optimization, a performance-oriented or economic cost criterion is minimized or maximized over a finite horizon while the usual control specifications enter as constraints but not as set points. This approach integrates the computation of optimal set-point trajectories and of the regulation to these trajectories.
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Bibliography
Angeli D, Amrit R, Rawlings J (2012) On average performance and stability of economic model predictive control. IEEE Trans Autom Control 57(7):1615–1626
Bartusiak RD (2005) NMPC: a platform for optimal control of feed- or product-flexible manufacturing. Preprints International workshop on assessment and future directions of NMPC, Freudenstadt, pp 3–14
Diehl M, Amrit R, Rawlings J, Angeli D (2011) A Lyapunov function for economic optimizing model predictive control. IEEE Trans Autom Control 56(3):703–707
Engell S (2006, 2007) Feedback control for optimal process operation. Plenary paper IFAC ADCHEM, Gramado, 2006; J Process Control 17:203–219
Erdem G, Abel S, Morari M, Mazzotti M, Morbidelli M (2004) Automatic control of simulated moving beds. Part II: nonlinear isotherms. Ind Eng Chem Res 43:3895–3907
Finkler T, Lucia S, Dogru M, Engell S (2013) A simple control scheme for batch time minimization of exothermic semi-batch polymerizations. Ind Eng Chem Res 52:5906–5920
Finkler TF, Kawohl M, Piechottka U, Engell S (2014) Realization of online optimizing control in an industrial semi-batch polymerization. J Process Control 24:399–414
Grüne L (2013) Economic receding horizon control without terminal constraints. Automatica 49:725–734
Helbig A, Abel O, Marquardt W (2000) Structural concepts for optimization based control of transient processes. In: Nonlinear model predictive control. Allgöwer F and Zheng A, eds. Birkhäuser, Basel pp 295–311
Idris IAN, Engell S (2012) Economics-based NMPC strategies for the operation and control of a continuous catalytic distillation process. J Process Control 22:1832–1843
Lucia S, Finkler T, Basak D, Engell S (2013) A new Robust NMPC Scheme and its application to a semi-batch reactor example. J Process Control 23:1306–1319
Marlin TE, Hrymak AN (1997) Real-time operations optimization of continuous processes. In: Proceedings of CPC V, Lake Tahoe, AIChE symposium series, vol 93, pp 156–164
Morari M, Stephanopoulos G, Arkun Y (1980) Studies in the synthesis of control structures for chemical processes, part I. AIChE J 26:220–232
Ochoa S, Wozny G, Repke J-U (2010) Plantwide optimizing control of a continuous bioethanol production process. J Process Control 20:983–998.
Pham LC, Engell S (2011) A procedure for systematic control structure selection with application to reactive distillation. In: Proceedings of 18th IFAC world congress, Milan, pp 4898–4903
Rao CV, Rawlings JB, Mayne DQ (2003) Constrained state estimation for nonlinear discrete-time systems. IEEE Trans Autom Control 48:246–258
Rawlings J, Amrit R (2009) Optimizing process economic performance using model predictive control In: Nonlinear model predictive control – towards new challenging applications. Springer, Berlin, pp 119–138
Rolandi PA, Romagnoli JA (2005) A framework for online full optimizing control of chemical processes. In: Proceedings of ESCAPE 15. Barcelona, Elsevier, pp 1315–1320
Qin SJ, Badgwell TA (2003) A survey of industrial model predictive control technology. Control Eng Pract 11:733–764
Skogestad S (2000) Plantwide control: the search for the self-optimizing control structure. J Process Control 10:487–507
Toumi A, Engell S (2004) Optimization-based control of a reactive simulated moving bed process for glucose isomerization. Chem Eng Sci 59:3777–3792
Zanin AC, Tvrzska de Gouvea M, Odloak D (2000) Industrial implementation of a real-time optimization strategy for maximizing production of LPG in a FCC unit. Comput Chem Eng 24:525–531
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Engell, S. (2014). Model-Based Performance Optimizing Control. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, London. https://doi.org/10.1007/978-1-4471-5102-9_244-1
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DOI: https://doi.org/10.1007/978-1-4471-5102-9_244-1
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Latest
Model-Based Performance Optimizing Control- Published:
- 02 February 2021
DOI: https://doi.org/10.1007/978-1-4471-5102-9_244-2
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Original
Model-Based Performance Optimizing Control- Published:
- 10 October 2014
DOI: https://doi.org/10.1007/978-1-4471-5102-9_244-1