Efficient Plant Supervision Strategy Using NN Based Techniques

  • Ramon Ferreiro Garcia
  • Jose Luis Calvo Rolle
  • Francisco Javier Perez Castelo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6076)


Most of non-linear type one and type two control systems suffers from lack of detectability when model based techniques are applied on FDI (fault detection and isolation) tasks. In general, all types of processes suffer from lack of detectability also due to the ambiguity to discriminate the process, sensors and actuators in order to isolate any given fault. This work deals with a strategy to detect and isolate faults which include massive neural networks based functional approximation procedures associated to recursive rule based techniques applied to a parity space approach.


Backpropagation Conjugate Gradient Fault Detection Fault Isolation Neural Networks Parity Space Residual Generation 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Ramon Ferreiro Garcia
    • 1
  • Jose Luis Calvo Rolle
    • 2
  • Francisco Javier Perez Castelo
    • 2
  1. 1.ETSNM, Dept. Industrial Eng.University of La CorunaSpain
  2. 2.EUP, Dept. Industrial Eng.University of La CorunaSpain

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