Abstract
This paper presents the implementation of adaptive fuzzy neural network controller (FNNC) for accurate speed control of a permanent magnet synchronous motor (PMSM). FNNC includes neural network controller (NC) and fuzzy logic controller (FC). It combines the capability of fuzzy reasoning in handling uncertain information and the capability of neural network in learning from processes. The initial weights and biases of the artificial neural network (ANN) are obtained by offline training method. Using the output of the fuzzy controller (FC), online training is carried out to update the weights and biases of the ANN. Several results of simulation are provided to demonstrate the effectiveness of the proposed FNNC under the occurrence of parameter variations and external disturbance.
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© 2005 Springer-Verlag Berlin Heidelberg
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Cao, X., Zhu, J., Tang, R. (2005). Vector Controlled Permanent Magnet Synchronous Motor Drive with Adaptive Fuzzy Neural Network Controller. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3612. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539902_146
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DOI: https://doi.org/10.1007/11539902_146
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28320-1
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