Name
Abstract | ||
|---|---|---|
We present a framework for networked state estimation, where systems encode their (possibly high dimensional) state vectors using a mutually agreed basis between the system and the estimator (in a remote monitoring unit). The basis sparsifies the state vectors, i.e., it represents them using vectors with few non-zero components, and as a result, the systems might need to transmit only a fraction of the original information to be able to recover the non-zero components of the transformed state vector. Hence, the estimator can recover the state vector of the system from an under-determined linear set of equations. We use a greedy search algorithm to calculate the sparsifying basis. Then, we present an upper bound for the estimation error. Finally, we demonstrate the results on a numerical example. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.3182/20130925-2-DE-4044.00050 | IFAC Proceedings Volumes |
Keywords | Field | DocType |
Networked Estimation,System state estimation,State monitoring,Sparsifying basis,Uncertain linear systems | ENCODE,Mathematical optimization,State vector,Upper and lower bounds,Communications system,Greedy algorithm,Mathematics,Estimator | Journal |
Volume | Issue | ISSN |
46 | 27 | 1474-6670 |
Citations | PageRank | References |
0 | 0.34 | 16 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Farhad Farokhi | 1 | 95 | 22.77 |
| Amirpasha Shirazinia | 2 | 62 | 6.90 |
| Karl Henrik Johansson | 3 | 3996 | 322.75 |