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Moberg, Stig
Publications (10 of 30) Show all publications
Hedberg, E., Norrlöf, M., Moberg, S. & Gunnarsson, S. (2018). Comparing Feedback Linearization and Jacobian Linearization for LQ Control of an Industrial Manipulator. In: Proccedings of the 12TH IFAC SYMPOSIUM ON ROBOT CONTROL: . Paper presented at 12TH IFAC SYMPOSIUM ON ROBOT CONTROL.
Open this publication in new window or tab >>Comparing Feedback Linearization and Jacobian Linearization for LQ Control of an Industrial Manipulator
2018 (English)In: Proccedings of the 12TH IFAC SYMPOSIUM ON ROBOT CONTROL, 2018Conference paper, Published paper (Refereed)
Abstract [en]

Feedback linearization is compared to Jacobian linearization for LQ control of atwo-link industrial manipulator. A method for obtaining equivalent nominal performance forboth control designs is introduced. An experimentally verified benchmark model with industrialrelevance is used for comparing the designs. Results do not show any conclusive advantages ofFeedback linearization.

National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-151588 (URN)
Conference
12TH IFAC SYMPOSIUM ON ROBOT CONTROL
Available from: 2018-09-25 Created: 2018-09-25 Last updated: 2018-10-19
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
Moberg, S. (2010). Modeling and Control of Flexible Manipulators. (Doctoral dissertation). Linköping: Linköping University Electronic Press
Open this publication in new window or tab >>Modeling and Control of Flexible Manipulators
2010 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Industrial robot manipulators are general-purpose machines used for industrial automation in order to increase productivity, flexibility, and product quality. Other reasons for using industrial robots are cost saving, and elimination of hazardous and unpleasant work. Robot motion control is a key competence for robot manufacturers, and the current development is focused on increasing the robot performance, reducing the robot cost, improving safety, and introducing new functionalities.  Therefore, there is a need to continuously improve the mathematical models and control methods in order to fulfil conflicting requirements, such as increased performance of a weight-reduced robot, with lower mechanical stiffness and more complicated vibration modes. One reason for this development of the robot mechanical structure is of course cost-reduction, but other benefits are also obtained, such as lower environmental impact, lower power consumption, improved dexterity, and higher safety.

This thesis deals with different aspects of modeling and control of flexible, i.e., elastic, manipulators. For an accurate description of a modern industrial manipulator, this thesis shows that the traditional flexible joint model, described in literature, is not sufficient. An improved model where the elasticity is described by a number of localized multidimensional spring-damper pairs is therefore proposed. This model is called the extended flexible joint model. The main contributions of this work are the design and analysis of identification methods, and of inverse dynamics control methods, for the extended flexible joint model.

The proposed identification method is a frequency-domain non-linear gray-box method, which is evaluated by the identification of a modern six-axes robot manipulator. The identified model gives a good description of the global behavior of this robot.

The inverse dynamics problem is discussed, and a solution methodology is proposed. This methodology is based on the solution of a differential algebraic equation (DAE). The inverse dynamics solution is then used for feedforward control of both a simulated manipulator and of a real robot manipulator.

The last part of this work concerns feedback control. First, a model-based nonlinear feedback control (feedback linearization) is evaluated and compared to a model-based feedforward control algorithm. Finally, two benchmark problems for robust feedback control of a flexible manipulator are presented and some proposed solutions are analyzed.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2010. p. 101
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1349
Keywords
Modeling, identification, control, robot manipulator, DAE, flexible multibody dynamics, inverse dynamics, benchmark
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-60831 (URN)978-91-7393-289-9 (ISBN)
Public defence
2010-12-03, Sal Visionen, Hus B, Campus Valla, Linköping University, Linköping, 10:15 (English)
Opponent
Supervisors
Available from: 2010-11-18 Created: 2010-10-27 Last updated: 2010-11-18Bibliographically approved
Moberg, S., Öhr, J. & Gunnarsson, S. (2009). A Benchmark Problem for Robust Feedback Control of a Flexible Manipulator. IEEE Transactions on Control Systems Technology, 17(6), 1398-1405
Open this publication in new window or tab >>A Benchmark Problem for Robust Feedback Control of a Flexible Manipulator
2009 (English)In: IEEE Transactions on Control Systems Technology, ISSN 1063-6536, E-ISSN 1558-0865, Vol. 17, no 6, p. 1398-1405Article in journal (Refereed) Published
Abstract [en]

A benchmark problem for robust feedback control of a flexible manipulator is presented. The system to be controlled is a four-mass system subject to input saturation, nonlinear gear elasticity, model uncertainties, and load disturbances affecting both the motor and the arm. The system should be controlled by a discrete-time controller that optimizes performance for given robustness requirements. Four suggested solutions are presented, and even though the solutions are based on different design methods, they give comparable results.

Keywords
Flexible structures, Manipulators, Position control, Robots, Robustness
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-51596 (URN)10.1109/TCST.2008.2006755 (DOI)
Available from: 2009-11-09 Created: 2009-11-09 Last updated: 2017-12-12
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
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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
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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
Wallén, J., Gunnarsson, S., Norrlöf, M., Henriksson, R. & Moberg, S. (2009). ILC Applied to a Flexible Two-Link Robot Model using Sensor-Fusion-Based Estimates. In: Proceedings of 48th IEEE Conference on Decision and Control: . Paper presented at 48th IEEE Conference on Decision and Control, Shanghai, China, December, 2009 (pp. 458-463). IEEE
Open this publication in new window or tab >>ILC Applied to a Flexible Two-Link Robot Model using Sensor-Fusion-Based Estimates
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2009 (English)In: Proceedings of 48th IEEE Conference on Decision and Control, IEEE , 2009, p. 458-463Conference paper, Published paper (Refereed)
Abstract [en]

Estimates from an extended Kalman filter (EKF) is used in an Iterative Learning Control (ILC) algorithm applied to a realistic two-link robot model with flexible joints. The angles seen from the arm side of the joints (arm angles) are estimated by an EKF in two ways: 1) using  measurements of angles seen from the motor side of the joints (motor angles), which normally  are the only measurements available in commercial industrial robot systems, 2) using both motor- angle and tool-acceleration measurements. The estimates are then used in an ILC algorithm. The results show that the actual arm angles are clearly improved compared to when only motor angles are used in the ILC update, even though model errors are introduced.

Place, publisher, year, edition, pages
IEEE, 2009
Series
I E E E Conference on Decision and Control, Including the Symposium on Adaptive Processes. Proceedings, ISSN 0191-2216
Keywords
Iterative learning control, MIMO robot model, Estimate
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-53462 (URN)10.1109/CDC.2009.5400864 (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
Available from: 2010-01-22 Created: 2010-01-22 Last updated: 2013-12-03
Wallén, J., Gunnarsson, S., Henriksson, R., Moberg, S. & Norrlöf, M. (2009). ILC Applied to a Flexible Two-Link Robot Model using Sensor-Fusion-Based Estimates. Linköping: Linköping University Electronic Press
Open this publication in new window or tab >>ILC Applied to a Flexible Two-Link Robot Model using Sensor-Fusion-Based Estimates
Show others...
2009 (English)Report (Other academic)
Abstract [en]

Estimates from an extended Kalman filter (EKF) is used in an Iterative Learning Control (ILC) algorithm applied to a realistic two-link robot model with flexible joints. The angles seen from the arm side of the joints (arm angles) are estimated by an EKF in two ways: 1) using  measurements of angles seen from the motor side of the joints (motor angles), which normally  are the only measurements available in commercial industrial robot systems, 2) using both motor- angle and tool-acceleration measurements. The estimates are then used in an ILC algorithm. The results show that the actual arm angles are clearly improved compared to when only motor angles are used in the ILC update, even though model errors are introduced.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2009. p. 9
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2880
Keywords
Iterative learning control; Robotics; Sensor fusion
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-56194 (URN)LiTH-ISY-R-2880 (ISRN)
Available from: 2010-04-30 Created: 2010-04-30 Last updated: 2014-10-01Bibliographically approved
Moberg, S. & Hanssen, S. (2009). Inverse Dynamics of Flexible Manipulators. In: Proceedings of the 2009 Conference on Multibody Dynamics: . Paper presented at 2009 Conference on Multibody Dynamics, Warsaw, Poland, 29th June - 2nd July, 2009 (pp. 1-20).
Open this publication in new window or tab >>Inverse Dynamics of Flexible Manipulators
2009 (English)In: Proceedings of the 2009 Conference on Multibody Dynamics, 2009, p. 1-20Conference paper, Published paper (Refereed)
Abstract [en]

High performance robot manipulators, in terms of cycle time and accuracy, require well designed control methods, based on accurate dynamic models. Robot manipulators are traditionally described by the flexible joint model or the flexible link model. These models only consider elasticity in the rotational direction. When these models are used for control or simulation, the accuracy can be limited due to the model simplifications, since a real manipulator has a distributed flexibility inall directions. This work investigates different methods for the inverse dynamics of a more general manipulator model, called the extended flexible joint model. The inverse dynamics solution is needed for feedforward control, which is often used for high-precision robot manipulator control.

The inverse dynamics of the extended flexible joint model can be computed as the solution of a high-index differential algebraic equation (DAE). One method is to solve the discretized DAE using a constant stepsize constant-order backwards differentiation formula (BDF). This work shows that there is only a small difference between solving theoriginal high-index DAE and the index-reduced DAE. It is also concluded that scaling of the algebraic equations and their derivatives is important.

The inverse dynamics can be solved as an initial-value problem if the zero dynamics of the system is stable, i.e., minimum phase. For unstable zero dynamics, an optimization approach based on the discretized DAE is suggested. An optimization method, using a continuous DAE formulation, is also suggested and evaluated. The solvers are illustrated by simulation, using a manipulator with two actuators and five degrees-of-freedom.

Keywords
Manipulator, Control, Differential algebraic equation, Flexible multibody dynamics, Non-minimum phase, Inverse dynamics
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-61326 (URN)
Conference
2009 Conference on Multibody Dynamics, Warsaw, Poland, 29th June - 2nd July, 2009
Funder
Swedish Research Council
Available from: 2010-11-12 Created: 2010-11-12 Last updated: 2013-09-16
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