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ILC applied to a flexible two-link robot model using sensor-fusion-based estimates

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5 Author(s)
Johanna Wallén ; Division of Automatic Control, Department of Electrical Engineering, Linköping University, SE-58183, Sweden ; Svante Gunnarsson ; Robert Henriksson ; Stig Moberg
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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.

Published in:

Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on

Date of Conference:

15-18 Dec. 2009