Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference |
| Subtitle of host publication | CDC-ECC '05 |
| Place of Publication | Seville, Spain |
| Pages | 3357-3362 |
| Number of pages | 6 |
| Publication status | Published - 2005 |
| Event | 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05 - Seville, Spain Duration: 12 Dec 2005 → 15 Dec 2005 |
Abstract
The problem of high measurement noise in identification issue is treated in this paper for an innovative parallel robotic manipulator. To consider the noise and the correlation across the system's output a complete statistical approach is presented. The Maximum-Likelihood estimator is used for the identification of the dynamics parameters. Furthermore the experiments were designed based on a statistical criterion, such that the resulting excitation trajectories minimize the uncertainty bounds of the estimation. The experimental results are consequently compared with those resulting from classic deterministic approaches. This comparison demonstrates that the presented methodology yields bias-free and asymptotic efficient estimation.
ASJC Scopus subject areas
- Engineering(all)
- General Engineering
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Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference: CDC-ECC '05. Seville, Spain, 2005. p. 3357-3362 1582680.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Statistical approach for bias-free identification of a parallel manipulator affected by large measurement noise
AU - Abdellatif, Houssem
AU - Heimann, Bodo
AU - Grotjahn, Martin
PY - 2005
Y1 - 2005
N2 - The problem of high measurement noise in identification issue is treated in this paper for an innovative parallel robotic manipulator. To consider the noise and the correlation across the system's output a complete statistical approach is presented. The Maximum-Likelihood estimator is used for the identification of the dynamics parameters. Furthermore the experiments were designed based on a statistical criterion, such that the resulting excitation trajectories minimize the uncertainty bounds of the estimation. The experimental results are consequently compared with those resulting from classic deterministic approaches. This comparison demonstrates that the presented methodology yields bias-free and asymptotic efficient estimation.
AB - The problem of high measurement noise in identification issue is treated in this paper for an innovative parallel robotic manipulator. To consider the noise and the correlation across the system's output a complete statistical approach is presented. The Maximum-Likelihood estimator is used for the identification of the dynamics parameters. Furthermore the experiments were designed based on a statistical criterion, such that the resulting excitation trajectories minimize the uncertainty bounds of the estimation. The experimental results are consequently compared with those resulting from classic deterministic approaches. This comparison demonstrates that the presented methodology yields bias-free and asymptotic efficient estimation.
UR - http://www.scopus.com/inward/record.url?scp=33847220002&partnerID=8YFLogxK
U2 - 10.1109/CDC.2005.1582680
DO - 10.1109/CDC.2005.1582680
M3 - Conference contribution
AN - SCOPUS:33847220002
SN - 0780395689
SN - 9780780395688
SP - 3357
EP - 3362
BT - Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference
CY - Seville, Spain
T2 - 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05
Y2 - 12 December 2005 through 15 December 2005
ER -