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Wernholt, Erik
Publications (10 of 36) Show all publications
Moberg, S., Wernholt, E., Hanssen, S. & Brogårdh, T. (2014). Modeling and Parameter Estimation of Robot Manipulators using Extended Flexible Joint Models. Journal of Dynamic Systems Measurement, and Control, 136(3), 031005
Open this publication in new window or tab >>Modeling and Parameter Estimation of Robot Manipulators using Extended Flexible Joint Models
2014 (English)In: Journal of Dynamic Systems Measurement, and Control, ISSN 0022-0434, E-ISSN 1528-9028, Vol. 136, no 3, p. 031005-Article in journal (Refereed) Published
Abstract [en]

This paper considers the problem of dynamic modeling and identification of robot manipulators with respect to their elasticities. The so-called flexible joint model, modeling only the torsional gearbox elasticity, is shown to be insufficient for modeling a modern industrial manipulator accurately. The extended flexible joint model, where non-actuated joints are added to model the elasticity of the links and bearings, is used to improve the model accuracy. The unknown elasticity parameters are estimated using a frequency domain gray-box identification method. The conclusion is that the obtained model describes the movements of the motors and the tool mounted on the robot with significantly higher accuracy. Similar elasticity model parameters are obtained when using two different output variables for the identification, the motor position and the tool acceleration.

Keywords
Modeling, flexible arms, calibration and identification, motion control, robot manipulator.
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-61667 (URN)10.1115/1.4026300 (DOI)000333588100005 ()
Available from: 2010-11-17 Created: 2010-11-17 Last updated: 2017-12-12
Wernholt, E. & Moberg, S. (2011). Nonlinear Gray-Box Identification Using Local Models Applied to Industrial Robots. Automatica, 47(4), 650-660
Open this publication in new window or tab >>Nonlinear Gray-Box Identification Using Local Models Applied to Industrial Robots
2011 (English)In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 47, no 4, p. 650-660Article in journal (Refereed) Published
Abstract [en]

In this paper, we study the problem of estimating unknown parameters in nonlinear gray-box models that may be multivariable, nonlinear, unstable, and resonant at the same time. A straightforward use of time-domain predication-error methods for this type of problem easily ends up in a large and numerically stiff optimization problem. We therefore propose an identification procedure that uses intermediate local models that allow for data compression and a less complex optimization problem. The procedure is based on the estimation of the nonparametric frequency response function (FRF) in a number of operating points. The nonlinear gray-box model is linearized in the same operating points, resulting in parametric FRFs. The optimal parameters are finally obtained by minimizing the discrepancy between the nonparametric and parametric FRFs. The procedure is illustrated by estimating elasticity parameters in a six-axes industrial robot. Different parameter estimators are compared and experimental results show the usefulness of the proposed identification procedure. The weighted logarithmic least squares estimator achieves the best result and the identified model gives a good global description of the dynamics in the frequency range of interest for robot control.

Place, publisher, year, edition, pages
Elsevier, 2011
Keywords
System identification, Multivariable systems, Nonlinear systems, Closed-loop identification, Frequency response methods, Industrial robots
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-61670 (URN)10.1016/j.automatica.2011.01.021 (DOI)000289968500002 ()
Available from: 2010-11-17 Created: 2010-11-17 Last updated: 2017-12-12
Carvalho Bittencourt, A., Wernholt, E., Shiva, S.-T. & Brogårdh, T. (2010). An Extended Friction Model to Capture Load and Temperature Effects in Robot Joints. Linköping: Linköping University Electronic Press
Open this publication in new window or tab >>An Extended Friction Model to Capture Load and Temperature Effects in Robot Joints
2010 (English)Report (Other academic)
Abstract [en]

Friction is the result of complex interactions between contacting surfaces in a nanoscale perspective. Depending on the application, the different models available are more or less suitable. Available static friction models are typically considered to be dependent only on relative speed of interacting surfaces. However, it is known that friction can be affected by other factors than speed. In this paper, static friction in robot joints is studied with respect to changes in joint angle, load torque and temperature. The effects of these variables are analyzed by means of experiments on a standard industrial robot. Justified by their significance, load torque and temperature are included in an extended static friction model. The proposed model is validated in a wide operating range, reducing the average error a factor of 6 when compared to a standard static friction model.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2010. p. 9
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2948
Keywords
Friction, Modeling, Identification, Industrial robots
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-97593 (URN)LiTH-ISY-R-2948 (ISRN)
Available from: 2013-09-17 Created: 2013-09-17 Last updated: 2014-06-17Bibliographically approved
Carvalho Bittencourt, A., Wernholt, E., Sander-Tavallaey, S. & Brogårdh, T. (2010). An Extended Friction Model to capture Load and Temperature effects in Robot Joints. In: Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems: . Paper presented at 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan, 18-22 October, 2010 (pp. 6161-6167).
Open this publication in new window or tab >>An Extended Friction Model to capture Load and Temperature effects in Robot Joints
2010 (English)In: Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010, p. 6161-6167Conference paper, Published paper (Refereed)
Abstract [en]

Friction is the result of complex interactions between contacting surfaces in a nanoscale perspective. Depending on the application, the different models available are more or less suitable. Available static friction models are typically considered to be dependent only on relative speed of interacting surfaces. However, it is known that friction can be affected by other factors than speed. In this paper, static friction in robot joints is studied with respect to changes in joint angle, load torque and temperature. The effects of these variables are analyzed by means of experiments on a standard industrial robot. Justified by their significance, load torque and temperature are included in an extended static friction model. The proposed model is validated in a wide operating range, reducing the average error a factor of 6 when compared to a standard static friction model.

Keywords
Friction, Modeling, Identification, Industrial robots
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-62924 (URN)10.1109/IROS.2010.5650358 (DOI)978-1-4244-6674-0 (ISBN)
Conference
2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan, 18-22 October, 2010
Projects
LINK-SIC
Available from: 2010-12-07 Created: 2010-12-07 Last updated: 2013-09-17
Axelsson, P., Norrlöf, M., Wernholt, E. & Gustafsson, F. (2010). Extended Kalman Filter Applied to Industrial Manipulators. In: Proceedings of Reglermöte 2010: . Paper presented at Reglermötet 2010, Lund, Sweden, 8-9 June, 2010.
Open this publication in new window or tab >>Extended Kalman Filter Applied to Industrial Manipulators
2010 (English)In: Proceedings of Reglermöte 2010, 2010Conference paper, Published paper (Other academic)
Abstract [en]

This paper summarizes previous work on tool position estimation on industrial manipulators, and emphasize the problems that must be taken care of in order to get a satisfied result. The acceleration of the robot tool, measured by an accelerometer, together with measurements of motor angles are used. The states are estimated with an extended Kalman filter. A method for tuning the covariance matrices for the noise, used in the observer, is suggested. The work has been focused on a robot with two degrees of freedom.

Keywords
Extended Kalman Filter, Industrial manipulator, Accelerometer
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-88981 (URN)
Conference
Reglermötet 2010, Lund, Sweden, 8-9 June, 2010
Projects
Vinnova Excellence Center LINK-SIC at Linkoping University, Sweden
Available from: 2013-02-19 Created: 2013-02-19 Last updated: 2013-07-09
Henriksson, R., Norrlöf, M., Moberg, S., Wernholt, E. & Schön, T. (2009). Experimental Comparison of Observers for Tool Position Estimation of Industrial Robots. Linköping: Linköping University Electronic Press
Open this publication in new window or tab >>Experimental Comparison of Observers for Tool Position Estimation of Industrial Robots
Show others...
2009 (English)Report (Other academic)
Abstract [en]

This paper investigates methods for tool position estimation of industrial robots. It is assumed that the motor angular position and the tool acceleration are measured. The considered observers are different versions of the extended Kalman filter as well as a deterministic observer. A method for tuning the observers is suggested and the robustness of the methods is investigated. The observers are evaluated experimentally on a commercial industrial robot.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2009. p. 9
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2911
Keywords
Kalman filters, Angular measurement, Industrial robots, Nonlinear filters
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-56206 (URN)LiTH-ISY-R-2911 (ISRN)
Available from: 2010-04-30 Created: 2010-04-30 Last updated: 2014-10-01Bibliographically approved
Norrlöf, M., Henriksson, R., Moberg, S., Wernholt, E. & Schön, T. (2009). Experimental Comparison of Observers for Tool Position Estimation of Industrial Robots. In: Proceedings of the 48th IEEE Conference on Decision and Control: . Paper presented at 48th IEEE Conference on Decision and Control, Shanghai, China, December, 2009 (pp. 8065-8070).
Open this publication in new window or tab >>Experimental Comparison of Observers for Tool Position Estimation of Industrial Robots
Show others...
2009 (English)In: Proceedings of the 48th IEEE Conference on Decision and Control, 2009, p. 8065-8070Conference paper, Published paper (Refereed)
Abstract [en]

This paper investigates methods for tool position estimation of industrial robots. It is assumed that the motor angular position and the tool acceleration are measured. The considered observers are different versions of the extended Kalman filter as well as a deterministic observer. A method for tuning the observers is suggested and the robustness of the methods is investigated. The observers are evaluated experimentally on a commercial industrial robot.

Keywords
Kalman filters, Angular measurement, Industrial robots, Nonlinear filters
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-50662 (URN)10.1109/CDC.2009.5400313 (DOI)978-1-4244-3872-3 (ISBN)978-1-4244-3871-6 (ISBN)
Conference
48th IEEE Conference on Decision and Control, Shanghai, China, December, 2009
Projects
CADICS
Available from: 2009-10-13 Created: 2009-10-13 Last updated: 2013-07-06
Wernholt, E. & Gunnarsson, S. (2008). Estimation of Nonlinear Effects in Frequency Domain Identification of Industrial Robots. IEEE Transactions on Instrumentation and Measurement, 57(4), 856-863
Open this publication in new window or tab >>Estimation of Nonlinear Effects in Frequency Domain Identification of Industrial Robots
2008 (English)In: IEEE Transactions on Instrumentation and Measurement, ISSN 0018-9456, E-ISSN 1557-9662, Vol. 57, no 4, p. 856-863Article in journal (Refereed) Published
Abstract [en]

A method for the detection and estimation of nonlinear distortions when identifying multivariable frequency response functions (FRF) is considered. The method is successfully applied to experimental data from an industrial robot, collected in closed loop. The results show that nonlinear distortions are indeed present and cause larger variability in the FRF than the measurement noise contributions.

Place, publisher, year, edition, pages
IEEE Instrumentation and Measurement Society, 2008
Keywords
Frequency response functions, Industrial robots, Multivariable systems, Nonlinear distortions, Nonparametric identification
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-42259 (URN)10.1109/TIM.2007.911698 (DOI)62093 (Local ID)62093 (Archive number)62093 (OAI)
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2017-12-13
Wernholt, E. & Gunnarsson, S. (2008). Estimation of nonlinear effects in frequency-domain identification of industrial robots. In: IEEE Transactions on Instrumentation and Measurement, Braunschweig, Germany: (pp. 856-863).
Open this publication in new window or tab >>Estimation of nonlinear effects in frequency-domain identification of industrial robots
2008 (English)In: IEEE Transactions on Instrumentation and Measurement, Braunschweig, Germany, 2008, p. 856-863Conference paper, Published paper (Other academic)
Abstract [en]

A method for the detection and estimation of nonlinear distortions when identifying multivariable frequency response functions (FRF) is considered. The method is successfully applied to experimental data, which were collected in closed loop, from an industrial robot. The results show that nonlinear distortions are indeed present and cause larger variability in the FRF than the measurement-noise contributions.

Series
IEEE Transactions on Instrumentation and Measurement, ISSN 0018-9456
Keywords
closed loop systems, frequency response, frequency-domain analysis, industrial robots, nonlinear distortion, nonlinear effect estimation, multivariable frequency response function, closed loop, frequency domain identification, nonparametric identification, Frequency response functions (FRF)
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-12714 (URN)10.1109/TIM.2007.911698 (DOI)
Available from: 2007-10-30 Created: 2007-10-30 Last updated: 2009-05-18
Wernholt, E. & Moberg, S. (2008). Experimental Comparison of Methods for Multivariable Frequency Response Function Estimation. In: Proceedings of the 17th IFAC World Congress: . Paper presented at 17th IFAC Worlds Congress, Seoul, Korea, July, 2008 (pp. 15359-15366).
Open this publication in new window or tab >>Experimental Comparison of Methods for Multivariable Frequency Response Function Estimation
2008 (English)In: Proceedings of the 17th IFAC World Congress, 2008, p. 15359-15366Conference paper, Published paper (Refereed)
Abstract [en]

Nonparametric estimation methods for the multivariable frequency response function are experimentally evaluated using closed-loop data from an industrial robot. Three classical estimators (H1, joint input-output, arithmetic mean) and two estimators based on nonlinear averaging techniques (harmonic mean, geometric/logarithmic mean) are considered. The estimators based on nonlinear averaging give the best results, followed by the arithmetic mean estimator, which gives a slightly larger bias. The joint input-output estimator, which is asymptotically unbiased in theory, turns out to give large bias errors for low frequencies. Finally, the H1 estimator gives the largest bias for all frequencies.

Keywords
System identification, Frequency response methods, Multivariable systems, Non-parametric identification, Closed-loop identification, Industrial robots
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-12713 (URN)10.3182/20080706-5-KR-1001.02598 (DOI)978-3-902661-00-5 (ISBN)
Conference
17th IFAC Worlds Congress, Seoul, Korea, July, 2008
Available from: 2007-10-30 Created: 2007-10-30 Last updated: 2013-09-15
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