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Automated Feed-Forward Learning for Pressure-Compensated Mobile Hydraulic Valves With Significant Dead-Zone

[+] Author Affiliations
Jarmo Nurmi, Jouni Mattila

Tampere University of Technology, Tampere, Finland

Paper No. FPMC2017-4258, pp. V001T01A027; 10 pages
  • ASME/BATH 2017 Symposium on Fluid Power and Motion Control
  • ASME/BATH 2017 Symposium on Fluid Power and Motion Control
  • Sarasota, Forida, USA, October 16–19, 2017
  • Conference Sponsors: Fluid Power Systems and Technology Division
  • ISBN: 978-0-7918-5833-2
  • Copyright © 2017 by ASME


Hydraulic manipulators on mobile machines, whose hydraulic actuators are usually controlled by mobile hydraulic valves, are being considered for robotic closed-loop control. A feed-forward-based strategy combining position and velocity feedback has been found to be an effective method for the motion control of pressure-compensated mobile hydraulic valves that have a significant dead zone. The feed-forward can be manually identified. However, manually identifying the feed-forward models for each valve-actuator pair is often very time-consuming and error-prone. For this practical reason, we propose an automated feed-forward learning method based on velocity and position feedback. We present experimental results for a heavy-duty hydraulic manipulator on a forest forwarder to demonstrate the effectiveness of the proposed method. These results motivate the automated identification of velocity feed-forward models for motion control of heavy-duty hydraulic manipulators controlled by pressure-compensated mobile hydraulic valves that have a significant input dead zone.

Copyright © 2017 by ASME



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