Moment based model predictive control for systems with additive uncertainty

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

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Samenvatting

In this paper, we present a model predictive control (MPC) strategy based on the moments of the state variables and the cost functional. The statistical properties of the state predictions are calculated through the open loop iteration of dynamics and used in the formulation of MPC cost function. We show that the moment based formulation yields predictive control problems which are computationally simpler to solve compared to the existing robust MPC formulations, while providing statistical robustness properties. We apply the proposed MPC technique to a simple simulation example to demonstrate its effectiveness.

Originele taal-2Engels
Titel2017 American Control Conference, ACC 2017, 24-26 May 2017, Seattle, Washington
Plaats van productiePiscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's3072-3077
Aantal pagina's6
ISBN van elektronische versie978-1-5090-5992-8
ISBN van geprinte versie978-1-5090-4583-9
DOI's
StatusGepubliceerd - 29 jun 2017
Evenement2017 American Control Conference (ACC 2017) - Sheraton Seattle Hotel, Seattle, Verenigde Staten van Amerika
Duur: 24 mei 201726 mei 2017
http://acc2017.a2c2.org/

Congres

Congres2017 American Control Conference (ACC 2017)
Verkorte titelACC 2017
LandVerenigde Staten van Amerika
StadSeattle
Periode24/05/1726/05/17
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