Extended and Unscented Kalman Filtering Applied to a Flexible-Joint Robot with Jerk Estimation

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 f...

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Main Authors: Mohammad Ali Badamchizadeh, Iraj Hassanzadeh, Mehdi Abedinpour Fallah
Format: Article
Language:English
Published: Wiley 2010-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2010/482972
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author Mohammad Ali Badamchizadeh
Iraj Hassanzadeh
Mehdi Abedinpour Fallah
author_facet Mohammad Ali Badamchizadeh
Iraj Hassanzadeh
Mehdi Abedinpour Fallah
author_sort Mohammad Ali Badamchizadeh
collection DOAJ
description 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.
format Article
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institution Kabale University
issn 1026-0226
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language English
publishDate 2010-01-01
publisher Wiley
record_format Article
series Discrete Dynamics in Nature and Society
spelling doaj-art-399f73b7d3254d119c336c118b3a60d42025-02-03T01:09:49ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2010-01-01201010.1155/2010/482972482972Extended and Unscented Kalman Filtering Applied to a Flexible-Joint Robot with Jerk EstimationMohammad Ali Badamchizadeh0Iraj Hassanzadeh1Mehdi Abedinpour Fallah2Control Engineering Department, Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 5166614776, IranControl Engineering Department, Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 5166614776, IranDepartment of Mechanical and Industrial Engineering, Concordia University, Montreal, QC, H3G 1M8, CanadaRobust 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.http://dx.doi.org/10.1155/2010/482972
spellingShingle Mohammad Ali Badamchizadeh
Iraj Hassanzadeh
Mehdi Abedinpour Fallah
Extended and Unscented Kalman Filtering Applied to a Flexible-Joint Robot with Jerk Estimation
Discrete Dynamics in Nature and Society
title Extended and Unscented Kalman Filtering Applied to a Flexible-Joint Robot with Jerk Estimation
title_full Extended and Unscented Kalman Filtering Applied to a Flexible-Joint Robot with Jerk Estimation
title_fullStr Extended and Unscented Kalman Filtering Applied to a Flexible-Joint Robot with Jerk Estimation
title_full_unstemmed Extended and Unscented Kalman Filtering Applied to a Flexible-Joint Robot with Jerk Estimation
title_short Extended and Unscented Kalman Filtering Applied to a Flexible-Joint Robot with Jerk Estimation
title_sort extended and unscented kalman filtering applied to a flexible joint robot with jerk estimation
url http://dx.doi.org/10.1155/2010/482972
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AT irajhassanzadeh extendedandunscentedkalmanfilteringappliedtoaflexiblejointrobotwithjerkestimation
AT mehdiabedinpourfallah extendedandunscentedkalmanfilteringappliedtoaflexiblejointrobotwithjerkestimation