Recent Advances in Explicit Multiparametric Nonlinear Model Predictive Control

Luis F. Domínguez, Efstratios N. Pistikopoulos

Research output: Contribution to journalArticlepeer-review

27 Scopus citations


In this paper we present recent advances in multiparametric nonlinear programming (mp-NLP) algorithms for explicit nonlinear model predictive control (mp-NMPC). Three mp-NLP algorithms for NMPC are discussed, based on which novel mp-NMPC controllers are derived. The performance of the explicit controllers are then tested and compared in a simulation example involving the operation of a continuous stirred-tank reactor (CSTR). © 2010 American Chemical Society.
Original languageEnglish (US)
Pages (from-to)609-619
Number of pages11
JournalIndustrial & Engineering Chemistry Research
Issue number2
StatePublished - Jan 19 2011
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The authors are thankful for the financial support from the Mexican Council for Science and Technology (CONACyT), the European Research Council (MOBILE, ERC Advanced Grant, No: 226462), EPRSC (Grant EP/G059071/1), KAUST, and the CPSE Industrial Consortium.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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