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Automation of slewing motions for forestry cranes
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
2015 (English)In: 2015 15th International Conference on Control, Automation and Systems (ICCAS), IEEE, 2015, 796-801 p.Conference paper, Published paper (Refereed)
Abstract [en]

The modern timber harvesting industry would be ineffective without heavy duty advanced machinery used for logging. However, with benefits of mechanization comes the operation complexity. Introducing automation is expected to reduce the mental and physical load on the operator and improve the machine use efficiency. Nonetheless, with current technology fully autonomous timber harvesting is impossible. In this paper a semi-automation scenario is presented using the base joint actuator of a forestry forwarder crane taking into consideration the need to attenuate unwanted oscillations of its hanging grapple. We address the necessary motion planning and motion stabilization tasks. To reduce oscillations along a nominal trajectory, we design smooth reference profiles based on experiments. Meanwhile, a practical structure for a feedback controller is proposed and tested. In this process, actuator nonlinearities are dealt with feasible identification and compensation techniques.

Place, publisher, year, edition, pages
IEEE, 2015. 796-801 p.
Series
International Conference on Control Automation and Systems, ISSN 2093-7121
Keyword [en]
automation, forestry cranes, input nonlinearity, trajectory design, identification
National Category
Robotics
Research subject
Automatic Control
Identifiers
URN: urn:nbn:se:umu:diva-113791ISI: 000382295200164ISBN: 978-8-9932-1509-0 OAI: oai:DiVA.org:umu-113791DiVA: diva2:890164
Conference
15th International Conference on Control, Automation and Systems (ICCAS 2015) Oct. 13-16,2015 in BEXCO, Busan, Korea
Available from: 2015-12-31 Created: 2015-12-31 Last updated: 2017-10-04Bibliographically approved
In thesis
1. Towards semi-automation of forestry cranes: automated trajectory planning and active vibration damping
Open this publication in new window or tab >>Towards semi-automation of forestry cranes: automated trajectory planning and active vibration damping
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Forests represent one of the biggest terrestrial ecosystems of Earth, that can produce important raw renewable materials such as wood with the help of sun, air and water. To efficiently extract these raw materials, the tree harvesting process is highly mechanized in developed countries, meaning that advanced forestry machines are continuously used to fell, to process and to transport the logs and biomass obtained from the forests. However, working with these machines is demanding both mentally and physically, which are known factors to negatively affect operator productivity. Mental fatigue is mostly due to the manual operation of the on-board knuckleboom crane, which requires advanced cognitive work with two joystick levers, while the most serious physical strains arise from cabin vibrations. These vibrations are generated from knuckleboom crane vibrations as a result of aggressive manual operation.

To enhance operator workload, well-being, and to increase productivity of the logging process, semi-automation functions are suggested, which are supervised automatic executions of specific work elements. Some of the related issues are addressed in the current thesis. Therefore, the content is divided into: (1) the design and development of a semi-automation function focused only on the base joint actuator (slewing actuator) of a knuckleboom crane, and (2) active vibration damping solutions to treat crane structure vibrations induced by the main lift cylinder (inner boom actuator). The considered reference machine is a downsized knuckleboom crane of a forwarder machine, which is used to pick up log assortments from a harvesting site.

The proposed semi-automation function presented in the first part could be beneficial for operators to use during log loading/unloading scenarios. It consists from a closed-loop position control architecture, to which smooth reference slewing trajectories are provided by a trajectory planner that is automated via operator commands. The used trajectory generation algorithms are taken from conventional robotics and adapted to semi-automation context with proposed modifications that can be customizable by operators.

Further, the proposed active vibration damping solutions are aimed to reduce vibrations of the knuckleboom crane excited by the inner boom actuator due to aggressive manual commands. First, a popular input shaping control technique combined with a practical switching logic was investigated to deal with the excited payload oscillations. This technique proved to be useful with a fixed crane pose, however it did not provide much robustness in terms of different link configurations. To tackle this problem an H2-optimal controller is developed, which is active in the pressure feedback-loop and its solely purpose is to damp the same payload oscillations. During the design process, operator commands are treated and explained from input disturbance viewpoint.

All of the hypothesis throughout this thesis were verified with extensive experimental studies using the reference machine.

Place, publisher, year, edition, pages
Umeå: Umeå universitet, 2017. 85 p.
Series
Robotics and control lab, ISSN 1654-5419 ; 9
Keyword
Forestry, forwarder cranes, semi-automation, slewing actuator, automated trajectory planning, oscillations, inner boom actuator, active vibration damping, frequency estimation, input shaping control technique, H2-optimal control
National Category
Control Engineering Robotics
Identifiers
urn:nbn:se:umu:diva-140256 (URN)978-91-7601-776-0 (ISBN)
Public defence
2017-10-27, N420, Naturvetarhuset, Umeå, 13:00 (English)
Opponent
Supervisors
Available from: 2017-10-06 Created: 2017-10-04 Last updated: 2017-10-13Bibliographically approved

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Citation style
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