Title :
T-S fuzzy modeling of interior permanent magnet synchronous motor
Author :
Wang, Fa Guang ; Park, Seung Kyu ; Yoon, Taesung ; Ahn, Ho Kyun
Author_Institution :
Dept. of Electr. Eng., Changwon Nat. Univ., Changwon, South Korea
fDate :
Nov. 29 2010-Dec. 1 2010
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 :
fuzzy set theory; permanent magnet motors; regression analysis; T-S fuzzy modeling; constrained function; fuzzy c-regression model; parameter uncertainty; permanent magnet synchronous motor; series linear model; IPMSM; T-S fuzzy model; feedback; identification; linear model; nonlinear system;
Conference_Titel :
Intelligent Systems Design and Applications (ISDA), 2010 10th International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-8134-7
DOI :
10.1109/ISDA.2010.5687268