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A Parallelizable Algorithm for Stabilizing Large Sparse Linear Systems With Uncertain Interconnections
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DOI：10.1109/ACCESS.2022.3164250.png)
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Abstract
En 中文
This paper proposes a new method for permuting sparse matrices into an upper block triangular from. The algorithm is highly parallelizable, which makes it suitable for large-scale systems with uncertain interconnection patterns. In such cases, the proposed decomposition can be used to develop flexible decentralized control strategies that produce a different gain matrix whenever the configuration changes. Applications to interconnected microgrids and supply and demand networks are provided to illustrate the versatility of the proposed approach.
Keywords:
Sparse matrices
Decentralized control
Matrix decomposition
Linear systems
Large-scale systems
Topology
Stability analysis
Large-scale systems
reconfigurable interconnections
uncertainty
decentralized control
sparse matrices
block triangular structure
parallel graph theoretic decompositions
Journal
IF:
3.6
Papers:
9.8W
Citations:
29.4W
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