Stability Analysis of the Neural Network Based Fault Tolerant Control for the Boiler Unit

  • Andrzej Czajkowski
  • Krzysztof Patan
  • Józef Korbicz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7268)


This paper deals with the stability analysis of the fault accommodation control system. When a fault is detected, the fault tolerant control tries to compensate the fault effect by adding to the standard control the auxiliary signal. This auxiliary control constitutes the additional control loop which can influence the stability of the entire control system. This paper focuses on the stability analysis of proposed control scheme based on the Lyapunov direct method.


Fault Diagnosis Model Predictive Control State Space Model Propose Control Scheme Fault Tolerant Control 
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  1. 1.
    Blanke, M., Kinnaert, M., Lunze, J., Staroswiecki, M.: Diagnosis and Fault-Tolerant Control. Springer, Berlin (2006)zbMATHGoogle Scholar
  2. 2.
    Bonfé, M., Castaldi, P., Mimmo, N., Simani, S.: Active fault tolerant control of nonlinear systems: The cart-pole example. International Journal of Applied Mathematics and Computer Science 21(3), 441–445 (2011)MathSciNetzbMATHCrossRefGoogle Scholar
  3. 3.
    Czajkowski, A., Patan, K.: Robust fault detection and accommodation of the boiler unit using state space neural networks. In: Diagnostics of Processes and Systems - DPS 2011: 10th International Science and Technology Conference, p. [10]. [B. m.], Zamość, Polska (2011)Google Scholar
  4. 4.
    Ducard, G.: Fault-tolerant flight control and guidance systems: practical methods for small unmanned aerial vehicles. Advances in Industrial Control. Springer (2009),
  5. 5.
    Isermann, R.: Fault Diagnosis Applications: Model Based Condition Monitoring, Actuators, Drives, Machinery, Plants, Sensors, and Fault-tolerant Systems. Springer (2011)Google Scholar
  6. 6.
    Korbicz, J., Koscielny, J.M., Kowalczuk, Z., Cholewa, W. (eds.): Fault Diagnosis. Models, Artificial Intelligence, Applications. Springer, Berlin (2004)zbMATHGoogle Scholar
  7. 7.
    Löfberg, J.: Yalmip: A Toolbox for Modeling and Optimization in MATLAB. In: Proceedings of the CACSD Conference, Taipei, Taiwan (2004),
  8. 8.
    Nørgaard, M., Ravn, O., Poulsen, N.K., Hansen, L.K.: Neural Networks for Modelling and Control of Dynamic Systems. Springer, London (2000)CrossRefGoogle Scholar
  9. 9.
    Noura, H., Theilliol, D., Ponsart, J., Chamseddine, A.: Fault-tolerant Control Systems: Design and Practical Applications. Advances in Industrial Control. Springer (2009)Google Scholar
  10. 10.
    Patan, K.: Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes. Springer, Berlin (2008)Google Scholar
  11. 11.
    Patan, K.: Local stability conditions for discrete-time cascade locally recurrent neural networks. International Journal of Applied Mathematics and Computer Science 20, 23–34 (2010)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Patan, K., Korbicz, J.: Nonlinear model predictive control of a boiler unit: a fault tolerant control study. In: Conference on Control and Fault-Tolerant Systems - SysTol 2010 [CD–ROM]. [B. m.], Nice, Francja, pp. 738–743 (2010) ISBN: 978-1-4244-8152-1Google Scholar
  13. 13.
    Puig, V.: Fault diagnosis and fault tolerant control using set-membership approaches: Application to real case studies. International Journal of Applied Mathematics and Computer Science 20(4), 619–635 (2010)MathSciNetzbMATHCrossRefGoogle Scholar
  14. 14.
    Sturm, J.F.: Using SEDUMI 1.02, a MATLAB* toolbox for optimization over symmetric cones (2001),
  15. 15.
    Theillol, D., Cédric, J., Zhang, Y.: Actuator fault tolerant control design based on reconfigurable reference input. International Journal of Applied Mathematics and Computer Science 18, 553–560 (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Andrzej Czajkowski
    • 1
  • Krzysztof Patan
    • 1
  • Józef Korbicz
    • 1
  1. 1.Institute of Control and Computation EngineeringUniversity of Zielona GóraZielona GóraPoland

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