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A fuzzy expert system for predicting the performance of SR motor
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| Author(s) |
B. Mirzaeian; M. Moallem |
| Abstract |
In this paper a fuzzy expert system for predicting the performance of a switched reluctance motor has been developed. The design vector consists of design parameters. Output performance variables are efficiency and torque ripple. Improved Magnetic Equivalent Circuit (IMEC) method has been used to generate the input-output data. The input-output data is used to produce the initial fuzzy rules for predicting the performance of Switched Reluctance Motor (SRM). The initial set of fuzzy rules with triangular membership functions has been devised using a table look-up scheme. This set of fuzzy rules has been optimized to a set of fuzzy rules with Gaussian membership functions using gradient descent training scheme. The performance prediction results for a 6/8, 4kw, SR motor shows good agreement with the results obtained from IMEC method or Finite Element (FE) analysis. |
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| Filename: | EPE2001 - PP00567 - Moallem.pdf |
| Filesize: | 505.1 KB |
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| Type |
Members Only |
| Date |
Last modified 2004-03-10 by System |
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