This paper proposes a novel hierarchical coalitional MPC technique, where transitions to the best communication topology are considered over the prediction horizon. For this reason, a new variable, called transition horizon, is added to the optimization problem to compute the optimal instant to introduce a new topology. Consequently, local controllers can anticipate topology transitions and adapt their trajectories whilst optimizing their local interests. Furthermore, stability guarantees in the closed-loop control of each coalition are provided. The benefits of this control method are shown via a simulated non-linear eight-coupled tanks plant. Copyright (C) 2020 The Authors.

Coalitional MPC with predicted topology transitions

Eva Masero;
2020-01-01

Abstract

This paper proposes a novel hierarchical coalitional MPC technique, where transitions to the best communication topology are considered over the prediction horizon. For this reason, a new variable, called transition horizon, is added to the optimization problem to compute the optimal instant to introduce a new topology. Consequently, local controllers can anticipate topology transitions and adapt their trajectories whilst optimizing their local interests. Furthermore, stability guarantees in the closed-loop control of each coalition are provided. The benefits of this control method are shown via a simulated non-linear eight-coupled tanks plant. Copyright (C) 2020 The Authors.
2020
Proceedings of the 21st IFAC World Congress
Model predictive control
Multi-agent systems
Networked control
LMI
Stability
File in questo prodotto:
File Dimensione Formato  
Paper_CoalitionalMPCwithPredictedTopologyTransitions.pdf

accesso aperto

: Publisher’s version
Dimensione 492.3 kB
Formato Adobe PDF
492.3 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1254537
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 4
  • ???jsp.display-item.citation.isi??? 4
social impact