Statistical approach for bias-free identification of a parallel manipulator affected by large measurement noise

verfasst von

Houssem Abdellatif, Bodo Heimann, Martin Grotjahn

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.

Organisationseinheit(en)

Institut für Mechatronische Systeme

Externe Organisation(en)

IAV GmbH

Typ

Aufsatz in Konferenzband

Seiten

3357-3362

Anzahl der Seiten

6

Publikationsdatum

2005

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Ingenieurwesen (insg.)

Elektronische Version(en)

https://doi.org/10.1109/CDC.2005.1582680 (Zugang: Geschlossen)