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Journal of Dynamic Systems, Measurement, and Control | Volume 129 | Issue 3 | TECHNICAL PAPERS
TECHNICAL PAPERS

Independent Identification of Friction Characteristics for Parallel Manipulators

[+] Author and Article Information
Houssem Abdellatif1

 Hannover Center of Mechatronics, Appelstr. 11, D-30167 Hannover, Germanyabdellatif@mzh.uni-hannover.de

Martin Grotjahn, Bodo Heimann

 Hannover Center of Mechatronics, Appelstr. 11, D-30167 Hannover, Germany

1

Corresponding author.

J. Dyn. Sys., Meas., Control 129(3), 294-302 (Aug 28, 2006) (9 pages) doi:10.1115/1.2718242 History: Received September 02, 2005; Revised August 28, 2006
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The compensation for friction or joint losses in robotic manipulators contributes to an important improvement of the control quality. Besides appropriate friction modeling, experimental identification of the model parameters is fundamental toward better control performance. Conventionally steady-state friction characteristics are investigated for mechanical systems in the first step. However, and due to the high kinematic coupling, such procedure is already complicated for complex multiple closed-loop mechanisms, like parallel manipulators. Actuation friction of such mechanisms becomes configuration dependent. This paper presents a methodology that deals with such challenge. The kinematic coupling is regarded in the friction model and therefore in the design of the experimental identification. With the proposed strategy, it is possible to identify the steady-state friction parameters independently from any knowledge about inertial or rigid-body dynamics. Friction models for sensorless passive joints can also be provided. Besides, the method is kept very practical, since there is no need for any additional hardware devices or interfaces than a standard industrial control. The suitability for the industrial field is proven by experimental application to PaLiDA that is a six degrees of freedom parallel manipulator equipped with linear directly driven actuators.
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References

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Figures

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+General scheme of the kinematics for parallel manipulators
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General scheme of the kinematics for parallel manipulators
Figure 1

General scheme of the kinematics for parallel manipulators

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+Calculated rigid-body forces for a typical motion with constant end-effector velocity
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Calculated rigid-body forces for a typical motion with constant end-effector velocity
Figure 2

Calculated rigid-body forces for a typical motion with constant end-effector velocity

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+Distribution of configurations in workspace with related PTP trajectories, used for the identification of friction parameters
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Distribution of configurations in workspace with related PTP trajectories, used for the identification of friction parameters
Figure 5

Distribution of configurations in workspace with related PTP trajectories, used for the identification of friction parameters

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+The PKM PaLiDA. Left panel: test bed at the Hannover industrial fair 2001. Right panel: CAD model.
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The PKM PaLiDA. Left panel: test bed at the Hannover industrial fair 2001. Right panel: CAD model.
Figure 6

The PKM PaLiDA. Left panel: test bed at the Hannover industrial fair 2001. Right panel: CAD model.

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+Velocity-force characteristics for PaLiDA. (◻) Measured actuation forces, (-∙-) fitted local model, (∘) measured forces after compensation of centrifugal effects, and (- - -) fitted local model after compensation of centrifugal effects.
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Velocity-force characteristics for PaLiDA. (◻) Measured actuation forces, (-∙-) fitted local model, (∘) measured forces after compensation of centrifugal effects, and (- - -) fitted local model after compensation of centrifugal effects.
Figure 7

Velocity-force characteristics for PaLiDA. (◻) Measured actuation forces, (-∙-) fitted local model, (∘) measured forces after compensation of centrifugal effects, and (- - -) fitted local model after compensation of centrifugal effects.

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+Used trajectories for the identification of local friction characteristics
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Used trajectories for the identification of local friction characteristics
Figure 3

Used trajectories for the identification of local friction characteristics

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+For identification motion calculated active joint variables and passive joint variables. The validated data correspond to close area, so that averaging is admissible.
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For identification motion calculated active joint variables and passive joint variables. The validated data correspond to close area, so that averaging is admissible.
Figure 4

For identification motion calculated active joint variables and passive joint variables. The validated data correspond to close area, so that averaging is admissible.

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+Configuration dependent force-velocity characteristics for single actuator. (∘) measured forces and (—) fitted local model. The x axis of all figures refers to the actuator velocity (m/s), y axis corresponds to the actuator force (N).
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Configuration dependent force-velocity characteristics for single actuator. (∘) measured forces and (—) fitted local model. The x axis of all figures refers to the actuator velocity (m/s), y axis corresponds to the actuator force (N).
Figure 8

Configuration dependent force-velocity characteristics for single actuator. (∘) measured forces and (—) fitted local model. The x axis of all figures refers to the actuator velocity (m/s), y axis corresponds to the actuator force (N).

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+A strut of the PKM PaLiDA with the respective passive and active joints
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A strut of the PKM PaLiDA with the respective passive and active joints
Figure 9

A strut of the PKM PaLiDA with the respective passive and active joints

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+Measured (thick line) versus calculated forces. Thin line: only rigid-body model, medium line: with additional friction forces.
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Measured (thick line) versus calculated forces. Thin line: only rigid-body model, medium line: with additional friction forces.
Figure 10

Measured (thick line) versus calculated forces. Thin line: only rigid-body model, medium line: with additional friction forces.

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+Experimental results: improvement of control accuracy by friction compensation (thick line) compared to compensation of rigid-body dynamics only (middle line) and by using simple PID control (thin line)
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Experimental results: improvement of control accuracy by friction compensation (thick line) compared to compensation of rigid-body dynamics only (middle line) and by using simple PID control (thin line)
Figure 11

Experimental results: improvement of control accuracy by friction compensation (thick line) compared to compensation of rigid-body dynamics only (middle line) and by using simple PID control (thin line)

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