Artículo
Stochastic model predictive control for tracking linear systems
D' Jorge, Agustina; Santoro, Bruno F.; Anderson, Alejandro Luis
; González, Alejandro Hernán
; Ferramosca, Antonio
Fecha de publicación:
04/2019
Editorial:
John Wiley & Sons Ltd
Revista:
Optimal Control Applications & Methods
ISSN:
0143-2087
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
This note presents a stochastic formulation of the model predictive control for tracking (MPCT), based on the results of the work of Lorenzen et al. The proposed controller ensures constraints satisfaction in probability, and maintains the main features of the MPCT, that are feasibility for any changing setpoints and enlarged domain of attraction, even larger than the one delivered by Lorenzen et al, thanks to the use of artificial references and relaxed terminal constraints. The asymptotic stability (in probability) of the minimal robust positively invariant set centered on the desired setpoint is guaranteed. Simulations on a DC-DC converter show the benefits and the properties of the proposal.
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Articulos(CCT - SANTA FE)
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - SANTA FE
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - SANTA FE
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; Santoro, Bruno F.; Anderson, Alejandro Luis; González, Alejandro Hernán; Ferramosca, Antonio; Stochastic model predictive control for tracking linear systems; John Wiley & Sons Ltd; Optimal Control Applications & Methods; 4-2019
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