.png){kind=icon}
Return
Scalable distributed model predictive control for constrained systems
.png){kind=icon}
OA
AI
DOI：10.1016/j.automatica.2018.03.050.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
A distributed model predictive control strategy is proposed for subsystems sharing a limited resource. Self-organized Time Division Multiple Access is used to coordinate subsystem controllers in a sequence such that no two re-optimize simultaneously. This new approach requires no central coordination or pre-organized optimizing sequence. The scheme guarantees satisfaction of coupled constraints despite dynamic entry and exit of subsystems. (C) 2018 Elsevier Ltd. All rights reserved.
Keywords:
Distributed model predictive control
Constrained systems
Scalable DMPC
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
5.9
Papers:
1.2W
Citations:
5.2W
Organization
Cited Papers
ShareSaveShareSaveShareSaveCooperative distributed stochastic MPC for systems with state estimation and coupled probabilistic constraints.png)
AUTOMATICA
AUTOMATICAIF5.9
PREAI
ShareSaveCloning, expression and characterization of histidine-tagged biotin synthase of Mycobacterium tuberculosisTuberculosis
TuberculosisIF0
PREAI
ShareSaveShareSave
View more