.png){kind=icon}
Return
Distributed static output feedback robust model predictive control for process networks
.png){kind=icon}
OA
AI
DOI：10.1016/j.conengprac.2022.105239.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper formulates a distributed static output feedback robust model predictive control for process networks to solve problems relating to unmeasured states and interconnected couplings. The initial conditions on the couplings are predicted by previous information and the boundedness of the predicted error is proved. In light of the static output feedback design conditions, the distributed static output feedback robust model predictive control is designed by transforming an infinite time optimization problem into a tractably solved one. The solvability of the optimization problem and the stability are proved to underpin the proposed approach. Simulations and an experimental case study are provided to validate the effectiveness of the proposed approach.
Keywords:
Robust model predictive control
Distributed static output feedback
Process networks
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4.6
Papers:
5.7K
Citations:
1.1W
Organization
Cited Papers
Output feedback robust MPC with one free control move for the linear polytopic uncertain system with bounded disturbance.png)
AUTOMATICA
AUTOMATICAIF5.9
PREAI
ShareSaveShareSaveA synthesis approach for output feedback robust constrained model predictive controlAUTOMATICA
AUTOMATICAIF5.9
PREAI
ShareSaveShareSaveDecentralised static output feedback stabilisation and synchronisation of networksAUTOMATICAOAAI
AUTOMATICAIF5.9
OAAIShareSaveShareSave
View more