This paper presents a novel clustering model predictive control technique where transitions to the best cooperation topology are planned over the prediction horizon. A new variable, the so-called transition horizon, is added to the optimization problem to calculate the optimal instant to introduce the next topology. Accordingly, agents can predict topology transitions to adapt their trajectories while optimizing their goals. Moreover, conditions to guarantee recursive feasibility and robust stability of the system are provided. Finally, the proposed control method is tested via a simulated eight-coupled tanks plant.

(2021). Robust coalitional model predictive control with predicted topology transitions [journal article - articolo]. In IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS. Retrieved from http://hdl.handle.net/10446/190514

Robust coalitional model predictive control with predicted topology transitions

Ferramosca, Antonio;
2021

Abstract

This paper presents a novel clustering model predictive control technique where transitions to the best cooperation topology are planned over the prediction horizon. A new variable, the so-called transition horizon, is added to the optimization problem to calculate the optimal instant to introduce the next topology. Accordingly, agents can predict topology transitions to adapt their trajectories while optimizing their goals. Moreover, conditions to guarantee recursive feasibility and robust stability of the system are provided. Finally, the proposed control method is tested via a simulated eight-coupled tanks plant.
articolo
Masero, Eva; Maestre, José M.; Ferramosca, Antonio; Francisco, Mario; Camacho, Eduardo F.
(2021). Robust coalitional model predictive control with predicted topology transitions [journal article - articolo]. In IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS. Retrieved from http://hdl.handle.net/10446/190514
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10446/190514
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