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Adaptive Nonlinear Control of an Asynchronous Machine using Neurone Networks Driven in Real Time
Journal of the Extendable Energies (Revue des Energies Renouvelables) / Proceeding of the First International Conference on The Energy Efficiency / ISSN 1112-2242, pp. 457-463 (2003)
  • Nadir Kabache
  • Boukhemis Chetate
Abstract
To avoid the various constraints related to the feddback linearisation control (FBLC), in this paper we propose a new control approach for the induction motor control based on artificial neural network (ANN) trained on-line. The two ANN are used for the on-line reconstitution of the state feedback nessary for the FBLC. The training rules used results from a combination between the ANN properties, the adaptative non-linear control propriety and the non-linear adaptation rules. Via thes three techniques a training rules were extracted, these last transform the tracking errors into a means to adjust the used ANN behaviour so that they adapt with the various operation modes of induction motor.
Keywords
  • Induction motor,
  • Neural networks,
  • Feedback linearisation,
  • Adaptative non linear control,
  • adaptation rules,
  • on-line training,
  • e1-modification
Publication Date
March, 2003
Citation Information
Nadir Kabache and Boukhemis Chetate. "Adaptive Nonlinear Control of an Asynchronous Machine using Neurone Networks Driven in Real Time" Journal of the Extendable Energies (Revue des Energies Renouvelables) / Proceeding of the First International Conference on The Energy Efficiency / ISSN 1112-2242, pp. 457-463 Vol. - Iss. - (2003)
Available at: http://works.bepress.com/nadir_kabache/6/