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A Comparison of a Neural Network and an Observer Approach for Detecting Faults in a Benchmark System

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Artificial Neural Nets and Genetic Algorithms

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Abstract

The detection of faults is considered for a class of nonlinear systems. A fault detection observer approach is compared to a neural network approach. Both approaches are applied to a an experimental ( benchmark) three-tank system.

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References

  1. Frank, P.M. (1994). On-line Fault Detection in Uncertain Nonlinear Systems Using Diagnostic Observers: A Survey. Int.J.Systems Sci, Vol. 25, pp. 2129–2154.

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  4. Shields, D.N. and S. Daley (1998). A Quantitative Fault Detection Method for a Class of Nonlinear Systems. Trans. Inst. MC 20(3), 125–133.

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  5. Yu, D. and D.N. Shields (1996). Bilinear Fault Detection Observer and its Application to a Hydraulic System. Int. Jnl. of Control, Vol. 64, pp. 1023–1047.

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Author information

Authors and Affiliations

  1. Maths-MIS, Coventry University, Priory St, Coventry, CV15FB, UK

    E. Gaura

Authors
  1. D. N. Shields
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  2. S. Du
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  3. E. Gaura
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Editor information

Editors and Affiliations

  1. Institute of Computer Science, Czech Republic

    Věra Kůrková  & Roman Neruda  & 

  2. Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, Prague, Czech Republic

    Miroslav Kárný

  3. Division of Mathematics, School of Mathematical and Information Sciences Coventry University, Coventry, UK

    Nigel C. Steele

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© 2001 Springer-Verlag Wien

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Shields, D.N., Du, S., Gaura, E. (2001). A Comparison of a Neural Network and an Observer Approach for Detecting Faults in a Benchmark System. In: Kůrková, V., Neruda, R., Kárný, M., Steele, N.C. (eds) Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6230-9_38

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  • DOI: https://doi.org/10.1007/978-3-7091-6230-9_38

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-83651-4

  • Online ISBN: 978-3-7091-6230-9

  • eBook Packages: Springer Book Archive

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