Title :
Research of PMSM Modeling Based on Least Square Support Vector Machines
Author :
Zhao, Jun ; Liu, Weiguo ; Tan, Bo
Author_Institution :
Coll. of Autom., Northwestern Polytech. Univ., Xi´´an, China
Abstract :
A modeling approach based on least square support vector machine (LSSVM) had been applied for permanent magnet synchronous motor (PMSM) and inverter with PMSM, which was multi-variable, nonlinear and coupled system. The modeling parameters with RBF kernel function was optimized by using cross validation method. The simulation result show that the tow modeling method is very effective. The maximum root mean square error (RMSE) of modeling of PMSM is 0.3196 and the maximum relative error is 0.2341%. And the maximum RMSE of modeling of inverter with PMSM is 0.4421 and the maximum relative error is 2.4121%. Using LSSVM for modeling of PMSM performs better forecast accuracy and successful modeling of PMSM.
Keywords :
invertors; least mean squares methods; permanent magnet motors; power engineering computing; radial basis function networks; support vector machines; synchronous motors; LSSVM; PMSM modeling; RBF kernel function; inverter; least square support vector machines; maximum root mean square error method; permanent magnet synchronous motors; Automation; Educational institutions; Integrated circuits; Inverters; Permanent magnet motors; Predictive models; Support vector machines; least square support vector machine; modeling; permanent magnet synchronous motor;
Conference_Titel :
Electrical and Control Engineering (ICECE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6880-5
DOI :
10.1109/iCECE.2010.983