Distributed Scalable Control for Large-Scale Networked Systems Using Chordal Decomposition
This letter proposes a distributed scalable control scheme for large-scale networked systems using chordal decomposition. To overcome the limitations caused by coupled subsystem structures, we develop a modeling framework for large-scale networked systems with arbitrary topological connections over directed graphs. Subsequently, leveraging the chordal decomposition theorem, we derive a sufficient condition for distributed scalable stabilization of such systems. Unlike traditional centralized or distributed control methods, the proposed approach inherently supports plug-and-play operations. Specifically, it eliminates the need to redesign all controller gains when the system undergoes partial modifications. Furthermore, the method improves computational efficiency while maintaining data confidentiality. Finally, the effectiveness of the proposed approach is validated through a coupled microgrid test system.
Authors
- An Lin (ORCID: https://orcid.org/0009-0000-5491-9483)
- Jun Cheng (ORCID: https://orcid.org/0000-0002-3483-747X)
- Chen Peng (ORCID: https://orcid.org/0000-0003-1232-6959)
Institutions
- Shanghai University (CN)
- Guangxi Normal University (CN)
Publication Details
- Journal
- IEEE Control Systems Letters
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/lcsys.2025.3586918
- Primary Topic
- Neural Networks Stability and Synchronization
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Foundation for Innovative Research Groups of the National Natural Science Foundation of China