Artículo
A robust gradient-based MPC for integrating real time optimizer (RTO) with control
Fecha de publicación:
06/2017
Editorial:
Elsevier
Revista:
Journal Of Process Control
ISSN:
0959-1524
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
A gradient-based model predictive control (MPC) strategy was recently proposed to reduce the computational burden derived from the explicit inclusion of an economic real time optimization (RTO). The main idea is to compute a suboptimal solution, which is the convex combination of a feasible solution and a solution of an approximated (linearized) problem. The main benefits of this strategy are that convergence is still guaranteed and good economic performances are obtained, according to several simulation scenarios. The formulation, however, is developed only for the nominal case, which significantly reduces its applicability. In this work, an extension of the gradient-based MPC to explicitly account for disturbances is made. The resulting robust formulation considers a nominal prediction model, but restricted constraints (in order to account for the effect of additive disturbances). The nominal economic performance is preserved and robust stability is ensured. An illustrative example shows the benefits of the proposal.
Palabras clave:
Model Predictive Control
,
Economic Optimization
,
Robust Control
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Articulos(INTEC)
Articulos de INST.DE DES.TECNOL.PARA LA IND.QUIMICA (I)
Articulos de INST.DE DES.TECNOL.PARA LA IND.QUIMICA (I)
Citación
D'jorge, Agustina; Ferramosca, Antonio; González, Alejandro Hernán; A robust gradient-based MPC for integrating real time optimizer (RTO) with control; Elsevier; Journal Of Process Control; 54; 6-2017; 65-80
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