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A Discrete‐Time VS Controller based on RBF Neural Networks for PMSM Drives
Author(s) -
Ciabattoni Lucio,
Corradini Maria Letizia,
Grisostomi Massimo,
Ippoliti Gianluca,
Longhi Sauro,
Orlando Giuseppe
Publication year - 2014
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.715
Subject(s) - control theory (sociology) , artificial neural network , differentiator , computer science , tracking error , control engineering , controller (irrigation) , engineering , control (management) , artificial intelligence , bandwidth (computing) , agronomy , biology , computer network
A method merging the features of variable structure control and neural network design is presented for speed control of a permanent magnet synchronous motor. The proposed control approach is based on a discrete‐time variable structure control and a robust digital differentiator for speed estimation. Radial basis function neural networks are used to learn about uncertainties affecting the system. A stability analysis is provided and the ultimate boundedness of the speed tracking error is proved. Control performance has been evaluated by simulations using the model of a commercial permanent magnet synchronous motor drive.