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Formalism to design a neural network: Application to an induction machine drive coupled to a non linear mechanical load

Published online by Cambridge University Press:  15 November 2000

C. Forgez ,
B. Lemaire-Semail  and
J. P. Hautier
C. Forgez
Affiliation:
Laboratoire d'Électrotechnique et d'Électronique de Puissance de Lille (L2EP), École Centrale de Lille, BP 48, 59651 Villeneuve d'Ascq Cedex, France
B. Lemaire-Semail*
Affiliation:
Laboratoire d'Électrotechnique et d'Électronique de Puissance de Lille (L2EP), EUDIL, avenue Paul Langevin, 59655 Villeneuve d'Ascq, France
J. P. Hautier
Affiliation:
Laboratoire d'Électrotechnique et d'Électronique de Puissance de Lille (L2EP), ENSAM, bd. Louis XIV, 59046 Lille Cedex, France
*
betty.semail@eudil.fr
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Abstract

This search deals with the control of a process in order to take into account non linearities without parameters identification. Neural networks properties are exploited for the modelling of non linear features, and a formalism is proposed to design a neural model which can be used directly as a controller. We apply this formalism to the modelling of a non linear mechanical load torque feature coupled to an induction machine in order to design a speed controller. A partial and a global neural method are presented. In order to overcome modelling errors or any process changes, an adaptive on line method is proposed. At last, simulation and experimental results are presented.

Keywords

Type
Research Article
Information
The European Physical Journal - Applied Physics , Volume 12 , Issue 2 , November 2000 , pp. 133 - 143
Copyright
© EDP Sciences, 2000

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