Robust Nonlinear Model Predictive Controller Based on Sensitivity Analysis - Application to a Continuous Photobioreactor

Abstract : This paper deals with the design of a predictive control law for microalgae culture process to regulate the biomass concentration at a chosen setpoint. However, the performances of the Nonlinear Model Predictive Controller usually decrease when the true plant evolution deviates significantly from that predicted by the model. Thus, a robust criterion under model's parameter uncertainties is considered, implying solving a min-max optimization problem. In order to reduce the computational burden and complexity induced by this formulation, a sensitivity functions analysis is carried out to determine the most influential parameters which will be considered in the optimization step. The proposed approach is validated in simulation and numerical results are given to illustrate its efficiency for setpoint tracking in the presence of parameter uncertainties.
Type de document :
Communication dans un congrès
IEEE MSC 2014, Oct 2014, Nice / Antibes, France. Proceedings of the 2014 IEEE Multi-Conference on Systems and Control
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https://hal-supelec.archives-ouvertes.fr/hal-01086558
Contributeur : Pascale Lepeltier <>
Soumis le : lundi 24 novembre 2014 - 14:30:23
Dernière modification le : jeudi 29 mars 2018 - 11:06:05

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  • HAL Id : hal-01086558, version 1

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Seif Eddine Benattia, Sihem Tebbani, Didier Dumur, Dan Selişteanu. Robust Nonlinear Model Predictive Controller Based on Sensitivity Analysis - Application to a Continuous Photobioreactor. IEEE MSC 2014, Oct 2014, Nice / Antibes, France. Proceedings of the 2014 IEEE Multi-Conference on Systems and Control. 〈hal-01086558〉

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