Code for publication: A general partitioning strategy for non-centralized control

DOI:10.4121/0e7dd651-66d7-451e-889b-d558e7d5b986.v1
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DOI: 10.4121/0e7dd651-66d7-451e-889b-d558e7d5b986
Datacite citation style:
Riccardi, Alessandro; Laurenti, Luca; De Schutter, Bart (2025): Code for publication: A general partitioning strategy for non-centralized control. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/0e7dd651-66d7-451e-889b-d558e7d5b986.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Software

Partitioning is a fundamental challenge for non-centralized control of large-scale systems, such as hierarchical, decentralized, distributed, and coalitional strategies. The problem consists of finding a decomposition of a network of dynamical systems into system units for which local controllers can be designed. Unfortunately, despite its critical role, a generalized approach to partitioning applicable to every system is still missing from the literature. This paper introduces a novel partitioning framework that integrates an algorithmic selection of fundamental system units (FSUs), considered indivisible entities, with an aggregative procedure, either algorithmic or optimization-based, to select composite system units (CSUs) made of several FSUs. A key contribution is the introduction of a global network metric, the partition index, which quantitatively balances intra- and inter-CSU interactions, with a granularity parameter accounting for the size of CSUs, allowing for their selection at different levels of aggregation. The proposed method is validated through case studies in distributed model predictive control (DMPC) for linear and hybrid systems, showing significant reductions in computation time and cost while maintaining or improving control performance w.r.t. conventional strategies.

History

  • 2025-03-03 first online, published, posted

Publisher

4TU.ResearchData

Format

*.py

Funding

  • CLariNet (grant code 101018826) [more info...] European Research Council

Organizations

TU Delft, Faculty of Mechanical Engineering, Delft Center for Systems and Control

To access the source code, use the following command:

git clone https://data.4tu.nl/v3/datasets/2246b13d-f3db-49ee-b9ab-264eb5584bba.git

Or download the latest commit as a ZIP.