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High speed on-line neural network control of an induction motor immune to analog circuit nonidealities

Publication ,  Journal Article
Liu, J; Burton, B; Kamran, F; Brooke, MA; Harley, RG; Habetler, TG
Published in: Proceedings - IEEE International Symposium on Circuits and Systems
January 1, 1997

A neural network using the Random Weight Change algorithm is shown able to be trained to perform on-line control of the current of an induction motor stator, despite analog circuit nonidealities. The induction motor is a complex nonlinear electromechanical system, with rapidly time-varying system parameters. Due to the small time constant of this power electronic system, the neural network must be able to finish each training cycle in less that 50 microseconds, which is only possible when controlled by specifically designed hardware circuits. An analog circuit is preferred for its ability to implement a reasonable size of network on one integrated chip. The analog circuit nonidealities are overcome by the Random Weight Change (RWC) algorithm. RWC is based on the method of random searching, and achieves similar performance to the back-propagation (BP) algorithm. The back-propagation algorithm is very difficult to implemented in analog hardware due to its sensitivity to offset and nonlinearity errors, the RWC algorithm is simulated with analog circuit nonidealities, and is shown immune to these problems, thus the RWC algorithm is found ideally suited for the high speed analog circuit neural network implementation.

Duke Scholars

Published In

Proceedings - IEEE International Symposium on Circuits and Systems

ISSN

0271-4310

Publication Date

January 1, 1997

Volume

1

Start / End Page

633 / 636
 

Citation

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Liu, J., Burton, B., Kamran, F., Brooke, M. A., Harley, R. G., & Habetler, T. G. (1997). High speed on-line neural network control of an induction motor immune to analog circuit nonidealities. Proceedings - IEEE International Symposium on Circuits and Systems, 1, 633–636.
Liu, J., B. Burton, F. Kamran, M. A. Brooke, R. G. Harley, and T. G. Habetler. “High speed on-line neural network control of an induction motor immune to analog circuit nonidealities.” Proceedings - IEEE International Symposium on Circuits and Systems 1 (January 1, 1997): 633–36.
Liu J, Burton B, Kamran F, Brooke MA, Harley RG, Habetler TG. High speed on-line neural network control of an induction motor immune to analog circuit nonidealities. Proceedings - IEEE International Symposium on Circuits and Systems. 1997 Jan 1;1:633–6.
Liu, J., et al. “High speed on-line neural network control of an induction motor immune to analog circuit nonidealities.” Proceedings - IEEE International Symposium on Circuits and Systems, vol. 1, Jan. 1997, pp. 633–36.
Liu J, Burton B, Kamran F, Brooke MA, Harley RG, Habetler TG. High speed on-line neural network control of an induction motor immune to analog circuit nonidealities. Proceedings - IEEE International Symposium on Circuits and Systems. 1997 Jan 1;1:633–636.

Published In

Proceedings - IEEE International Symposium on Circuits and Systems

ISSN

0271-4310

Publication Date

January 1, 1997

Volume

1

Start / End Page

633 / 636