An RBFNN-Based Direct Inverse Controller for PMSM with Disturbances
Considering the system uncertainties, such as parameter changes, modeling error, and external uncertainties, a radial basis function neural network (RBFNN) controller using the direct inverse method with the satisfactory stability for improving universal function approximation ability, convergence,...
Main Authors: | Shengquan Li, Juan Li, Yanqiu Shi |
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Format: | Article |
Language: | English |
Published: |
Hindawi-Wiley
2018-01-01
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Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2018/4034320 |
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