Abstract
A model reduction technique is presented that identifies and aggregates clusters in a large-scale network system and yields a reduced model with tractable dimension. The network clustering problem is translated to a graph reduction problem, which is formulated as a minimization of distance from lumpability. The problem is a non-convex, mixed-integer optimization problem and only depends on the graph structure of the system. We provide a heuristic algorithm to identify clusters that are not only suboptimal but are also connected, that is, each cluster forms a connected induced subgraph in the network system.
Original language | English |
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Title of host publication | 2019 IEEE 58th Conference on Decision and Control, CDC 2019 |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 5038-5043 |
Number of pages | 6 |
ISBN (Electronic) | 9781728113982 |
DOIs | |
Publication status | Published - 12 Mar 2020 |
Event | 58th IEEE Conference on Decision and Control (CDC 2019) - Nice, France Duration: 11 Dec 2019 → 13 Dec 2019 https://cdc2019.ieeecss.org/ |
Conference
Conference | 58th IEEE Conference on Decision and Control (CDC 2019) |
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Abbreviated title | CDC 2019 |
Country | France |
City | Nice |
Period | 11/12/19 → 13/12/19 |
Internet address |
Keywords
- clustering algorithm
- Large-scale systems
- lumpa-bility
- model reduction