A T-S Fuzzy Identification of Interior Permanent Magnet Synchronous

Faguang Wang,Minchan Kim, Hyunwoo Kim,Seungkyu Park,Taesung Yoon, Gunpyoung Kwak

Journal of the Korean Society for Precision Engineering(2011)

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摘要
Control of interior permanent magnet (IPMSM) is difficult because its nonlinearity and parameter uncertainty. In this paper, a fuzzy c-regression models clustering algorithm which is based on T-S fuzzy is used to model IPMSM with a series linear model and weight them by memberships. Lagrangian of constrained function is built for calculating clustering centers where training output data are considered. Based on these clustering centers, least square method is applied for T-S fuzzy linear model parameters. As a result, IPMSM can be modeled as T-S fuzzy model for T-S fuzzy control of them.
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关键词
nonlinear system,identification,linear model,feedback
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