Advertisement

Swing Trajectory Control for Large Excavators

  • A. W. Denman
  • P. R. McAree
  • M. P. Kearney
  • A. W. Reid
  • K. J. Austin
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 62)

Abstract

There is a strong push within the mining sector to automate equipment such as large excavators. A challenging problem is the control of motion on high inertia degrees of freedom where the actuators are constrained in the power they can deliver to and extract from the system and the machine’s underlying control system sits between the automation system and the actuators. The swing motion of an electric mining shovel is a good example. This paper investigates the use of predictive models to achieve minimum time swing motions in order to address the question what level of performance is possible in terms of realizing minimum time motions and accurate positional control. Experiments are described that explore these questions. The work described is associated with a project to automate an electricmining shovel and whilst the control law discussed here is a much simplified form of that used in this work, the experimental study sheds considerable light on the problem.

Keywords

State Space Model Switching Point Capture Region Predictive Controller Swing Angle 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    ABB Automation Products GmbH.: DCS Thyristor Power Converters for DC Drive Systems 25 to 5150/10300 A, Software Description, DCS600 MultiDrive (2002)Google Scholar
  2. 2.
    Gelb, A., Vander Velde, W.E.: Multiple-Input Describing Functions and Nonlinear System Design. McGraw-Hill Book Company, New York (1968)MATHGoogle Scholar
  3. 3.
    Graham, D., McRuer, D.: Analysis of Nonlinear Control Systems. John Wiley & Sons Inc., New York (1961)MATHGoogle Scholar
  4. 4.
    Hendricks, P.A., Keran, C.M.: Automation and Safety of Mobile Mining Equipment. Engineering nad Mining Journal (February 1995)Google Scholar
  5. 5.
    Hocking, L.M.: Optimal Control; An Introduction to the Theory with Applications. Oxford applied mathdmatics and computing science series, pp. 82–98 (1991)Google Scholar
  6. 6.
    Siegrist, P.M., McAree, P.R., Wallis, D.L., Kearney, M.P., van Geenhuizen, J.A.: Prediction Models for Collision Avoidance on Electric Mining Shovels. In: 2006 Australian Mining Technology Conference, Australia (September 2006)Google Scholar
  7. 7.
    Singh, S.: State of the Art in Automation of Earthmoving. In: Proceedings of the Wrokshop on Advanced Geomechatronics (October 2002)Google Scholar
  8. 8.
    Wauge, D.H.: Payload Estimation for Electric Mining Shovels. PhD thesis, Mechanical Engineering, University of Queensland (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • A. W. Denman
    • 1
  • P. R. McAree
    • 2
  • M. P. Kearney
    • 2
  • A. W. Reid
    • 2
  • K. J. Austin
    • 2
  1. 1.CRCMiningUniversity of QueenslandBrisbaneAustralia
  2. 2.No Institute Given 

Personalised recommendations