Design and Implementation of Adaptive Fuzzy Cerebellar Model Articulation Controller for Direct Torque Control System

This study implemented fuzzy control theory with a cerebellar controller to design a fuzzy cerebellar model articulation controller (FCMAC), ensuring system stability by deriving an adaptive FCMAC weight update rule from the Lyapunov theory. The speed estimator design in this study is based on the structure of an adaptive stator flux observer (ASFO) to achieve rapid sensorless control. According to results from experiments, installing the adaptive FCMAC speed controller in the induction motor’s direct torque control system demonstrates excellent speed dynamic response.

[1]  Kuo-Kai Shyu,et al.  Flux compensated direct torque control of induction motor drives for low speed operation , 2004, IEEE Transactions on Power Electronics.

[2]  R. Tilani,et al.  Univariate time series forecasting with fuzzy CMAC , 2004, Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826).

[3]  Hung-Ching Lu,et al.  Integrated structure design for CMAC-based fuzzy logic controller , 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

[4]  Chern-Lin Chen,et al.  Adaptive pseudoreduced-order flux observer for speed sensorless field-oriented control of IM , 1999, IEEE Trans. Ind. Electron..

[5]  Jan Melkebeek,et al.  Speed sensorless direct torque control of induction motors using an adaptive flux observer , 1999, Conference Record of the 1999 IEEE Industry Applications Conference. Thirty-Forth IAS Annual Meeting (Cat. No.99CH36370).