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A Vector Quantization Approach to Scenario Generation for Stochastic NMPC

  • Graham C. Goodwin
  • Jan Østergaard
  • Daniel E. Quevedo
  • Arie Feuer
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 384)

Abstract

This paper describes a novel technique for scenario generation aimed at closed loop stochastic nonlinear model predictive control. The key ingredient in the algorithm is the use of vector quantization methods.We also show how one can impose a tree structure on the resulting scenarios. Finally, we briefly describe how the scenarios can be used in large scale stochastic nonlinear model predictive control problems and we illustrate by a specific problem related to optimal mine planning.

Keywords

Scenario generation closed loop control stochastic nonlinear model predictive control vector quantization 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Graham C. Goodwin
    • 1
  • Jan Østergaard
    • 1
  • Daniel E. Quevedo
    • 1
  • Arie Feuer
    • 2
  1. 1.School of Electrical Engineering and Computer ScienceThe University of NewcastleAustralia
  2. 2.The TechnionHaifaIsrael

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