Faults tolerant control application using neural networks

  • Authors:
  • Lisbeth Perez;Francklin Rivas;Addison Rios;Gloria Mousalli

  • Affiliations:
  • Departamento de Sistemas de Control, Universidad de Los Andes, Mérida, Venezuela;Departamento de Sistemas de Control, Universidad de Los Andes, Mérida, Venezuela;Departamento de Sistemas de Control, Universidad de Los Andes, Mérida, Venezuela;Departamento de Medición y Evaluación, Universidad de Los Andes, Mérida, Venezuela

  • Venue:
  • CONTROL'07 Proceedings of the 3rd WSEAS/IASME international conference on Dynamical systems and control
  • Year:
  • 2007

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Abstract

In this work it is presented a fault tolerant control application using neural networks-based compensation schemes. The design consists of supervising the process possible faults using an observer that allows determining the present fault and its direction and then it will be used a classification neural network which will activate the appropriate controller according to the identified fault type. The plant to be controlled was the "Feedback Basic Process Rig 38-100", a completely self-contained pipes circuit which drives the water contained in the inferior tank to a smaller dimension and double compartment superior tank, by means of the motor pumping located in the inferior deposit. In this work it is controlled the superior tank water level.