Abstract
We consider the problem of identifying optimal sparse graph representations of dense consensus networks. The performance of the sparse representation is characterized by the global performance measure which quantifies the difference between the output of the sparse graph and the output of the original graph. By minimizing the sum of this performance measure and a sparsity-promoting penalty function, the alternating direction method of multipliers identifies sparsity structures that strike a balance between the performance measure and the number of edges in the graph. We then optimize the edge weights of sparse graphs over the identified topologies. Two examples are provided to illustrate the utility of the developed approach.
| Original language | English (US) |
|---|---|
| Title of host publication | 3rd IFAC Workshop on Distributed Estimation and Control in Networked Systems, NECSYS 2012 |
| Publisher | IFAC Secretariat |
| Pages | 305-310 |
| Number of pages | 6 |
| Edition | 26 |
| ISBN (Print) | 9783902823229 |
| DOIs | |
| State | Published - 2012 |
| Event | 3rd IFAC Workshop on Distributed Estimation and Control in Networked Systems, NECSYS 2012 - Santa Barbara, CA, United States Duration: Sep 14 2012 → Sep 15 2012 |
Publication series
| Name | IFAC Proceedings Volumes (IFAC-PapersOnline) |
|---|---|
| Number | 26 |
| Volume | 45 |
| ISSN (Print) | 1474-6670 |
Other
| Other | 3rd IFAC Workshop on Distributed Estimation and Control in Networked Systems, NECSYS 2012 |
|---|---|
| Country/Territory | United States |
| City | Santa Barbara, CA |
| Period | 9/14/12 → 9/15/12 |
Bibliographical note
Funding Information:★ Financial support from the National Science Foundation under CAREER Award CMMI-06-44793 and under awards CMMI-09-27720 and CMMI-0927509 is gratefully acknowledged.
Keywords
- Alternating direction method of multipliers
- Cardinality minimization
- Consensus networks
- Sparse graph representations
- Sparsity-promoting optimal control
- Structured feedback design