Trajectory optimization of a mining dragline using the method of Lagrange multipliers

McInnes, C. H. and Meehan, P. A. (2011) Trajectory optimization of a mining dragline using the method of Lagrange multipliers. International Journal of Robust and Nonlinear Control, 21 14: 1677-1692. doi:10.1002/rnc.1661

Author McInnes, C. H.
Meehan, P. A.
Title Trajectory optimization of a mining dragline using the method of Lagrange multipliers
Journal name International Journal of Robust and Nonlinear Control   Check publisher's open access policy
ISSN 1049-8923
Publication date 2011-09-25
Year available 2010
Sub-type Article (original research)
DOI 10.1002/rnc.1661
Open Access Status Not Open Access
Volume 21
Issue 14
Start page 1677
End page 1692
Total pages 16
Editor Mike Grimble
Place of publication Bognor Regis, West Sussex, U.K.
Publisher John Wiley & Sons
Language eng
Formatted abstract
The nonlinear coupled dynamic behaviour of a mining dragline is optimized to increase productivity and reduce metal fatigue on the boom. Draglines are very large crane-like robots used in open cut mining, primarily for the removal of overburden that covers a coal seam. The dynamic behaviour of the machine is a key determinant of productivity and fatigue-based maintenance. The Newton–Lagrange method is applied to a field-validated model to optimize slew torque under nonlinear constraints. Two scenarios are analysed: the minimization of cycle time with a time penalty for duty (estimated fatigue damage) and fixed rope lengths, and the minimization of duty under a fixed cycle time and measured rope lengths. The results from the second scenario compare favourably with earlier efforts to optimize slew torque using intuitive manual techniques. In particular, the numerical optimization procedure achieved a 50–60% reduction in duty, improving upon manual optimization results by 10–30%. Techniques are presented for solving convergence issues related to the high degree of nonlinearity of the model and constraints, actuator limitations and noise introduced by measured data.
Copyright © 2010 John Wiley & Sons, Ltd.
Keyword Mining
Constrained nonlinear optimization
Lagrange multipliers
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Article first published online: 5 NOV 2010.

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Mechanical & Mining Engineering Publications
Official 2011 Collection
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Created: Thu, 17 Mar 2011, 21:00:39 EST by Rose Clements on behalf of CRCMining