Pré-Publication, Document De Travail (Preprint/Prepublication) Année : 2026

Network-Realised Model Predictive Control Part I: NRF-Enabled Closed-loop Decomposition

Résumé

A two-layer control architecture is proposed to enable scalable implementations for constraint-based decision strategies, such as model predictive controllers. The bottom layer is based upon a distributed feedback-feedforward scheme that directs the controlled network's information flow according to a pre-specified communication infrastructure. Explicit expressions for the resulting closed-loop maps are obtained, and an offline model-matching procedure is proposed for designing the first layer. The obtained control laws are deployed via distributed state-space-based implementations, and the resulting closed-loop models enable predictive control design for the constraint management procedure described in our companion paper.

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Dates et versions

hal-04948143 , version 1 (14-02-2025)
hal-04948143 , version 2 (18-02-2025)
hal-04948143 , version 3 (23-12-2025)
hal-04948143 , version 4 (16-02-2026)
hal-04948143 , version 5 (10-04-2026)

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  • HAL Id : hal-04948143 , version 4

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Andrei Sperilă, Alessio Iovine, Sorin Olaru, Patrick Panciatici. Network-Realised Model Predictive Control Part I: NRF-Enabled Closed-loop Decomposition. 2026. ⟨hal-04948143v4⟩
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