Comparative analysis of intelligent controllers for high performance interior permanent magnet synchronous motor drive systems

Abstract

This paper provides a comparison among different intelligent controllers, particularly, fuzzy logic (FL), artificial neural network (ANN) and neuro-fuzzy (NF) controllers in terms of designing approach, implementation and performance for interior permanent magnet synchronous motor (IPMSM) drives. A radial basis function network (RBFN) is utilized as an ANN in this work. For NF control a fuzzy basis function network (FBFN) is developed in which the FL concepts are embedded. In order to provide a comparison, a closed loop vector control scheme for IPMSM incorporating intelligent controllers is successfully implemented in real-time using digital signal processor (DSP) board DS1102. The performances of various intelligent controllers are investigated and compared both in simulation and experiment. A review of intelligent controller applications for motor drive systems is also presented in this paper. Thus, this paper provides useful information for researchers and practicing engineers about intelligent controller applications for IPMSM drives.