M. Nasir Uddin
Speed control, fuzzy logic control, artificial neural network, neuro-fuzzy, proportional-integral controller, vector control, interior per-manent magnet synchronous motor, digital signal processor
This paper provides a design, implementation, and performance investigation of different intelligent controllers, particularly, fuzzy logic controller (FLC), artificial neural network (ANN), and neuro-fuzzy (NF) controllers for interior permanent magnet (IPM) synchronous motor (IPMSM) drive systems. A specific FLC is designed for the IPMSM drive based on motor dynamics and nonlinear load characteristics. A radial basis function network (RBFN) is utilized as an ANN. For NF control a fuzzy basis function network (FBFN) is developed in which the fuzzy logic concepts are embedded. In order to provide a demonstrative evidence of comparison, a closed loop vector control scheme for IPMSM incorporating intelligent controllers is successfully implemented in real-time using a digital signal processor (DSP) board DS1102. The performance of various intelligent controllers are investigated and compared both in simula- tion and experiment. A review of intelligent controller applications for motor drive systems is also presented in this paper. This paper intends to provide useful information for researchers and practicing engineers regarding intelligent controller applications in IPM motor drives.
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