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Adaptive backstepping control of a completely unknown permanent magnet motor
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| Author(s) |
KABZIŃSKI Jacek |
| Abstract |
We consider adaptive backstepping (AB) control of an interior permanent magnet (IPM) motor. We propose to use artificial neural networks, or neuro-fuzzy models to approximate unknown nonlinear functions in each stage of the backstepping procedure. In this case no regression matrix need to be found and "liner-in-the-parameter" assumption is not necessary. The last layer coefficients of the neural network are modified on-line by the differential adaptive law. We demonstrate that adaptive backstepping technique is able to control properly a completely unknown IPM machine. |
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| Filename: | 0679-epe2007-full-12420443.pdf |
| Filesize: | 328.2 KB |
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| Type |
Members Only |
| Date |
Last modified 2008-01-11 by System |
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