Modelling of Complex Systems for Control and Fault Diagnostics: A Knowledge Based Approach

  • Alexandros Soumelidis
  • András Edelmayer
Part of the Microprocessor-Based and Intelligent Systems Engineering book series (ISCA, volume 9)


Control and fault diagnostics of complex systems cannot be realized without a good methodology of modelling i.e. representing the structure and behaviour of the systems in the significant states of their operation. The conventional methods of large scale modelling require comprehensive knowledge about the system consisting of conform elements (e.g. a set of ordinary differential equations), and no gaps in the knowledge are allowed. Complex physical systems contain several types of elements and processes with different types of description and eventually gaps in the available knowledge. This paper presents the principles of a knowledge based approach of modelling of complex heterogeneous systems, and a possible realization by using Lisp and object oriented programming paradigms. This approach has been applied in a noise diagnostic expert system developed for use in pressurized water nuclear reactors.


artificial intelligence knowledge based systems intelligent control and diagnostics 


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Copyright information

© Springer Science+Business Media Dordrecht 1991

Authors and Affiliations

  • Alexandros Soumelidis
    • 1
  • András Edelmayer
    • 1
  1. 1.Systems and Controls LaboratoryComputer and Automation Institute of the Hungarian Academy of SciencesBudapest

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