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Model predictive control based on adaptive hinging hyperplanes model

  • Jun Xu*
  • , Xiaolin Huang
  • , Xiaomu Mu
  • , Shuning Wang
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The model of adaptive hinging hyperplanes (AHH) is used in model predictive control (MPC). The nonlinear dynamic system is approximated by the continuous piecewise affine (CPWA) model AHH and the controller design problem becomes a continuous piecewise quadratic programming. The necessary and sufficient conditions for a point to be locally optimal for such a problem are established, based on which, a descent algorithm is developed to find a local optimum. Issues concerning feasibility and stability are also discussed. Simulations are conducted to confirm the effectiveness of the proposed MPC strategy.

Original languageEnglish
Pages (from-to)1821-1831
Number of pages11
JournalJournal of Process Control
Volume22
Issue number10
DOIs
StatePublished - Dec 2012
Externally publishedYes

Keywords

  • Adaptive hinging hyperplanes
  • Local optimum
  • Model predictive control
  • Piecewise affine

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