Extension of First Order Predictive Functional Controllers to Handle Higher Order Internal Models

  • Authors:

  • Mohamed Khadir;John Ringwood

  • Affiliations:

  • Department of Computer Science, University Badji Mokhtar, Annaba, Algeria;Department of Electronic Engineering, National University of Ireland, Maynooth, Co. Kildare, Ireland

  • Venue:
  • International Journal of Applied Mathematics and Computer Science - Special Section: Selected Topics in Biological Cybernetics, Special Editors: Andrzej Kasiński and Filip Ponulak
  • Year:
  • 2008

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Abstract

Predictive Functional Control (PFC), belonging to the family of predictive control techniques, has been demonstrated as a powerful algorithm for controlling process plants. The input/output PFC formulation has been a particularly attractive paradigm for industrial processes, with a combination of simplicity and effectiveness. Though its use of a lag plus delay ARX/ARMAX model is justified in many applications, there exists a range of process types which may present difficulties, leading to chattering and/or instability. In this paper, instability of first order PFC is addressed, and solutions to handle higher order and difficult systems are proposed. The input/output PFC formulation is extended to cover the cases of internal models with zero and/or higher order pole dynamics in an ARX/ARMAX form, via a parallel and cascaded model decomposition. Finally, a generic form of PFC, based on elementary outputs, is proposed to handle a wider range of higher order oscillatory and non-minimum phase systems. The range of solutions presented are supported by appropriate examples.