文章基本信息

标题：Extended and Unscented Kalman Filtering Applied to a Flexible-Joint Robot with Jerk Estimation
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作者：Mohammad Ali Badamchizadeh ; Iraj Hassanzadeh ; Mehdi Abedinpour Fallah 等
期刊名称：Discrete Dynamics in Nature and Society
印刷版ISSN：1026-0226
电子版ISSN：1607-887X
出版年度：2010
卷号：2010
DOI：10.1155/2010/482972
出版社：Hindawi Publishing Corporation
摘要：Robust nonlinear control of flexible-joint robots requires that the link position, velocity, acceleration, and jerk be available. In this paper, we derive the dynamic model of a nonlinear flexible-joint robot based on the governing Euler-Lagrange equations and propose extended and unscented Kalman filters to estimate the link acceleration and jerk from position and velocity measurements. Both observers are designed for the same model and run with the same covariance matrices under the same initial conditions. A five-bar linkage robot with revolute flexible joints is considered as a case study. Simulation results verify the effectiveness of the proposed filters.