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A T-S Fuzzy Identification of Interior Permanent Magnet Synchronous  

Wang, Fa-Guang (Department of Electrical Engineering, Changwon Univ.)
Kim, Min-Chan (Department of Electrical Engineering, Changwon Univ.)
Kim, Hyun-Woo (Department of Electrical Engineering, Changwon Univ.)
Park, Seung-Kyu (Department of Electrical Engineering, Changwon Univ.)
Yoon, Tae-Sung (Department of Electrical Engineering, Changwon Univ.)
Kwak, Gun-Pyoung (Department of Electrical Engineering, Changwon Univ.)
Publication Information
Journal of the Korean Society for Precision Engineering / v.28, no.4, 2011 , pp. 391-397 More about this Journal
Abstract
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.
Keywords
T-S Fuzzy Model; Linear Model; Identification; Nonlinear System; Feedback; IPSM;
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