Nonlinear model predictive control of a boiler unit: A fault tolerant control study

Krzysztof Patan; Józef Korbicz

International Journal of Applied Mathematics and Computer Science (2012)

  • Volume: 22, Issue: 1, page 225-237
  • ISSN: 1641-876X

Abstract

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This paper deals with a nonlinear model predictive control designed for a boiler unit. The predictive controller is realized by means of a recurrent neural network which acts as a one-step ahead predictor. Then, based on the neural predictor, the control law is derived solving an optimization problem. Fault tolerant properties of the proposed control system are also investigated. A set of eight faulty scenarios is prepared to verify the quality of the fault tolerant control. Based of different faulty situations, a fault compensation problem is also investigated. As the automatic control system can hide faults from being observed, the control system is equipped with a fault detection block. The fault detection module designed using the one-step ahead predictor and constant thresholds informs the user about any abnormal behaviour of the system even in the cases when faults are quickly and reliably compensated by the predictive controller.

How to cite

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Krzysztof Patan, and Józef Korbicz. "Nonlinear model predictive control of a boiler unit: A fault tolerant control study." International Journal of Applied Mathematics and Computer Science 22.1 (2012): 225-237. <http://eudml.org/doc/208097>.

@article{KrzysztofPatan2012,
abstract = {This paper deals with a nonlinear model predictive control designed for a boiler unit. The predictive controller is realized by means of a recurrent neural network which acts as a one-step ahead predictor. Then, based on the neural predictor, the control law is derived solving an optimization problem. Fault tolerant properties of the proposed control system are also investigated. A set of eight faulty scenarios is prepared to verify the quality of the fault tolerant control. Based of different faulty situations, a fault compensation problem is also investigated. As the automatic control system can hide faults from being observed, the control system is equipped with a fault detection block. The fault detection module designed using the one-step ahead predictor and constant thresholds informs the user about any abnormal behaviour of the system even in the cases when faults are quickly and reliably compensated by the predictive controller.},
author = {Krzysztof Patan, Józef Korbicz},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {recurrent neural networks; process model; predictive control; fault detection; boiler unit},
language = {eng},
number = {1},
pages = {225-237},
title = {Nonlinear model predictive control of a boiler unit: A fault tolerant control study},
url = {http://eudml.org/doc/208097},
volume = {22},
year = {2012},
}

TY - JOUR
AU - Krzysztof Patan
AU - Józef Korbicz
TI - Nonlinear model predictive control of a boiler unit: A fault tolerant control study
JO - International Journal of Applied Mathematics and Computer Science
PY - 2012
VL - 22
IS - 1
SP - 225
EP - 237
AB - This paper deals with a nonlinear model predictive control designed for a boiler unit. The predictive controller is realized by means of a recurrent neural network which acts as a one-step ahead predictor. Then, based on the neural predictor, the control law is derived solving an optimization problem. Fault tolerant properties of the proposed control system are also investigated. A set of eight faulty scenarios is prepared to verify the quality of the fault tolerant control. Based of different faulty situations, a fault compensation problem is also investigated. As the automatic control system can hide faults from being observed, the control system is equipped with a fault detection block. The fault detection module designed using the one-step ahead predictor and constant thresholds informs the user about any abnormal behaviour of the system even in the cases when faults are quickly and reliably compensated by the predictive controller.
LA - eng
KW - recurrent neural networks; process model; predictive control; fault detection; boiler unit
UR - http://eudml.org/doc/208097
ER -

References

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Citations in EuDML Documents

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  1. Adam Nowicki, Michał Grochowski, Kazimierz Duzinkiewicz, Data-driven models for fault detection using kernel PCA: A water distribution system case study
  2. Jan Rybka, Artur Janicki, Comparison of speaker dependent and speaker independent emotion recognition
  3. Przemysław Śliwiński, Zygmunt Hasiewicz, Paweł Wachel, A simple scheme for semi-recursive identification of Hammerstein system nonlinearity by Haar wavelets
  4. Maciej Ławryńczuk, Nonlinear state-space predictive control with on-line linearisation and state estimation

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