Technical Communique: Who needs QP for linear MPC anyway?

  • Authors:

  • B. Kouvaritakis;M. Cannon;J. A. Rossiter

  • Affiliations:

  • Department of Engineering Science, Oxford University, Parks Road, Oxford OX1 3PJ, UK;Department of Engineering Science, Oxford University, Parks Road, Oxford OX1 3PJ, UK;Department of Mathematical Sciences, Loughborough University, Loughborough, Leic. LE11 3TP, UK

  • Venue:
  • Automatica (Journal of IFAC)
  • Year:
  • 2002

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Abstract

Conventional MPC uses quadratic programming (QP) to minimise, on-line, a cost over n linearly constrained control moves. However, stability constraints often require the use of large n thereby increasing the on-line computation, rendering the approach impracticable in the case of fast sampling. Here, we explore an alternative that requires a fraction of the computational cost (which increases only linearly with n), and propose an extension which, in all but a small class of models, matches to within a fraction of a percent point the performance of the optimal solution obtained through QP. The provocative title of the paper is intended to point out that the proposed approach offers a very attractive alternative to QP-based MPC.