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A T-S Fuzzy Identification of Interior Permanent Magnet Synchronous

Fa Guang Wang, Min Chan Kim, Hyun Woo Kim, Seung Kyu Park, Tae Sung Yoon, Gun Pyoung Kwak
JKSPE 2011;28(4):391-397.
Published online: April 1, 2011
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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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A T-S Fuzzy Identification of Interior Permanent Magnet Synchronous
J. Korean Soc. Precis. Eng.. 2011;28(4):391-397.   Published online April 1, 2011
Download Citation

Download a citation file in RIS format that can be imported by all major citation management software, including EndNote, ProCite, RefWorks, and Reference Manager.

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A T-S Fuzzy Identification of Interior Permanent Magnet Synchronous
J. Korean Soc. Precis. Eng.. 2011;28(4):391-397.   Published online April 1, 2011
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