A two-layer control architecture is proposed to enable scalable implementations for constraintbased 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 closedloop 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. (c) 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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