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Nonlinear Gray-Box Identification Using Local Models Applied to Industrial Robots
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2011 (English)In: Automatica, ISSN 0005-1098, Vol. 47, no 4, 650-660 p.Article 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. Vol. 47, no 4, 650-660 p.
Keyword [en]
System identification, Multivariable systems, Nonlinear systems, Closed-loop identification, Frequency response methods, Industrial robots
National Category
Control Engineering
URN: urn:nbn:se:liu:diva-61670DOI: 10.1016/j.automatica.2011.01.021ISI: 000289968500002OAI: diva2:370701
Available from: 2010-11-17 Created: 2010-11-17 Last updated: 2013-07-22
In thesis
1. Modeling and Control of Flexible Manipulators
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. 101 p.
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1349
Modeling, identification, control, robot manipulator, DAE, flexible multibody dynamics, inverse dynamics, benchmark
National Category
Control Engineering
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)
Available from: 2010-11-18 Created: 2010-10-27 Last updated: 2010-11-18Bibliographically approved

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