Extension of first order Predictive Functional Controllers to handle higher order internal models

Mohamed Tarek Khadir; John V. Ringwood

International Journal of Applied Mathematics and Computer Science (2008)

  • Volume: 18, Issue: 2, page 229-239
  • ISSN: 1641-876X

Abstract

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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.

How to cite

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Mohamed Tarek Khadir, and John V. Ringwood. "Extension of first order Predictive Functional Controllers to handle higher order internal models." International Journal of Applied Mathematics and Computer Science 18.2 (2008): 229-239. <http://eudml.org/doc/207880>.

@article{MohamedTarekKhadir2008,
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.},
author = {Mohamed Tarek Khadir, John V. Ringwood},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {model predictive control; predictive functional control; non-minimum phase systems; oscillatory systems},
language = {eng},
number = {2},
pages = {229-239},
title = {Extension of first order Predictive Functional Controllers to handle higher order internal models},
url = {http://eudml.org/doc/207880},
volume = {18},
year = {2008},
}

TY - JOUR
AU - Mohamed Tarek Khadir
AU - John V. Ringwood
TI - Extension of first order Predictive Functional Controllers to handle higher order internal models
JO - International Journal of Applied Mathematics and Computer Science
PY - 2008
VL - 18
IS - 2
SP - 229
EP - 239
AB - 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.
LA - eng
KW - model predictive control; predictive functional control; non-minimum phase systems; oscillatory systems
UR - http://eudml.org/doc/207880
ER -

References

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