Brief The nature of data pre-filters in MPC relevant identification-open- and closed-loop issues

  • Authors:

  • R. B. Gopaluni;R. S. Patwardhan;S. L. Shah

  • Affiliations:

  • Department of Chemical and Materials Engineering, 536 Chemical Mineral Eng. Building, University of Alberta, Edmonton, AB, Canada T6G 2G6;Department of Chemical and Materials Engineering, 536 Chemical Mineral Eng. Building, University of Alberta, Edmonton, AB, Canada T6G 2G6;Department of Chemical and Materials Engineering, 536 Chemical Mineral Eng. Building, University of Alberta, Edmonton, AB, Canada T6G 2G6

  • Venue:
  • Automatica (Journal of IFAC)
  • Year:
  • 2003

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Abstract

In this paper a model predictive control relevant identification (MRI) method is applied to a general class of linear PEM models and the effect of bias distribution on the multistep ahead predictions is studied. Good multistep ahead predictions are essential for model predictive controllers. Therefore, it is important to distribute the bias in such a way that it is compatible with the predictive control objective. This paper deals with the impact of MRI methods on the bias distribution and its effect on control loop performance.