This paper presents the use of a training algorithm based on a Lyapunov function approach applied to a stator current controller based on a state variable description of the induction machine plus a reference model. The results obtained with the proposed controller are compared with a previously reported method based on a Nonlinear Auto-Regressive Moving Average with eXogenous inputs (NARMAX) description of the induction machine. The proposed Lyapunov based training algorithm is used to ensure convergence of the weights towards a global minimum in the error function. Real time simulations employing a DSP based test bench are used to test the validity of the algorithms and the results are verified by a practical implementation of these controllers.
|Title of host publication
|Proceedings - 2015 IEEE 24th International Symposium on Industrial Electronics, ISIE 2015
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - 28 Sep 2015
|24th IEEE International Symposium on Industrial Electronics, ISIE 2015 - Buzios, Rio de Janeiro, Brazil
Duration: 3 Jun 2015 → 5 Jun 2015
|IEEE International Symposium on Industrial Electronics
|24th IEEE International Symposium on Industrial Electronics, ISIE 2015
|Buzios, Rio de Janeiro
|3/06/15 → 5/06/15
Bibliographical notePublisher Copyright:
© 2015 IEEE.
- Induction motor drives
- Lyapunov methods
- Neural Networks