A coalitional robust model predictive controller for tracking target sets is presented. The overall system is controlled by a set of local control agents that dynamically merge into cooperative coalitions or clusters so as to attain an efficient trade-off between cooperation burden and global performance optimality. Within each cluster, the agents coordinate their inputs to maximize their collective performance, while considering the coupling effect with external subsystems as uncertainty. By using a tube-based approach, the overall system state is driven to the target sets while satisfying state and input constraints despite the changes on the controllers clustering. Likewise, feasibility and stability of the closed-loop system are guaranteed by tracking techniques. The applicability of the proposed approach is illustrated by an academic example.

(2021). Distributed Model Predictive Control for Tracking: A Coalitional Clustering Approach [journal article - articolo]. In IEEE TRANSACTIONS ON AUTOMATIC CONTROL. Retrieved from http://hdl.handle.net/10446/199444

Distributed Model Predictive Control for Tracking: A Coalitional Clustering Approach

Ferramosca, Antonio;
2021-12-07

Abstract

A coalitional robust model predictive controller for tracking target sets is presented. The overall system is controlled by a set of local control agents that dynamically merge into cooperative coalitions or clusters so as to attain an efficient trade-off between cooperation burden and global performance optimality. Within each cluster, the agents coordinate their inputs to maximize their collective performance, while considering the coupling effect with external subsystems as uncertainty. By using a tube-based approach, the overall system state is driven to the target sets while satisfying state and input constraints despite the changes on the controllers clustering. Likewise, feasibility and stability of the closed-loop system are guaranteed by tracking techniques. The applicability of the proposed approach is illustrated by an academic example.
articolo
Chanfreut, Paula; Maestre, José Maria; Ferramosca, Antonio; Muros, Francisco Javier; Camacho, Eduardo F.
(2021). Distributed Model Predictive Control for Tracking: A Coalitional Clustering Approach [journal article - articolo]. In IEEE TRANSACTIONS ON AUTOMATIC CONTROL. Retrieved from http://hdl.handle.net/10446/199444
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/199444
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