Abstract
Operating cranes is challenging because the payload significantly lags behind the control input and can undergo large amplitude oscillations. While significant work has been directed at reducing the payload swing, little effort has been placed on reducing the time lag. There is a good reason for neglecting the time lag; it cannot be eliminated. It is a result of the physical limitations of the crane; motor torque limits coupled with the very large inertia of cranes and their payloads cause sluggish behavior. Experienced crane operators become accustomed to the time lag and develop the skill to start decelerating the crane well before the desired stopping location. This paper presents a control method that aids the human operator by graphically displaying a prediction of where the crane will stop. This predictive element is combined with an input-shaping controller that both reduces the payload swing and simplifies the implementation of the predictive element. Results from a study of crane operators show that the proposed control system significantly improves tower crane performance, in terms of both task completion time and positioning accuracy.
Original language | English |
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Article number | 5599310 |
Pages (from-to) | 323-330 |
Number of pages | 8 |
Journal | IEEE Transactions on Systems, Man, and Cybernetics Part A: Systems and Humans |
Volume | 41 |
Issue number | 2 |
DOIs | |
State | Published - Mar 2011 |
Externally published | Yes |
Funding
Manuscript received December 14, 2009; accepted April 23, 2010. Date of publication October 11, 2010; date of current version January 19, 2011. This work was supported in part by Siemens Energy and Automation, by Boeing Research and Technology, by the Japan Society for the Promotion of Science, and by Georgia Tech President’s Undergraduate Research Award. This paper was recommended by Associate Editor J. A. Adams. This work was supported in part by Siemens Energy and Automation, by Boeing Research and Technology, by the Japan Society for the Promotion of Science, and by Georgia Tech President's Undergraduate Research Award
Funders | Funder number |
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Boeing Research and Technology | |
Georgia Tech President | |
Siemens Energy and Automation | |
Japan Society for the Promotion of Science |
Keywords
- Human factors
- User interfaces
- Vibration control