arrow
Return

Robust coalitional model predictive control with plug-and-play capabilities

delete2023-07-01
delete4
delete
OA
AI
E
Eva Masero *
P
Pablo R. Baldivieso‐Monasterios
J
J. M. Maestre
P
Paul Trodden
DOI:10.1016/j.automatica.2023.111053delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
This article presents a distributed implementation of a model predictive controller with information exchange to manage a distributed networked system of coupled dynamic subsystems. We propose a coalitional control method, where local controllers coalesce into clusters to improve performance, as a tool to solve plug-and-play problems. Our main contribution is a tube-based coalitional approach that employs online optimized invariant sets. These sets are instrumental in guaranteeing recursive feasibility and stability when faced with plug-and-play operations, i.e., subsystems joining or leaving the network. We also explore the inherent robustness properties to absorb disturbances not covered by the tubes without the need to group local controllers. Finally, the simulation results show the benefits of our proposed control method.(c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keywords:
Distributed networked systems
Model predictive control
Control by clustering
Plug-and-play events
Tubes
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Automatica cover
Automatica
IF:
5.9
Papers:
1.2W
Citations:
5.2W

Organization

U
University of Sheffield
Scholars:
3.0W
Papers: 2.9W
Citations: 3.9W
U
University of Sevilla
Scholars:
1.9W
Papers: 1.7W
Citations: 15