| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 495142 | Applied Soft Computing | 2015 | 9 Pages |
•We propose an adaptive Takagi-Sugeno-Kang-fuzzy (TSK-fuzzy) speed controller (ATFSC) for use in direct torque control (DTC) induction motor (IM) drives to improve their dynamic responses.•The parameters of the TSK-fuzzy controller were adjusted online based on the adaptive rules derived in Lyapunov stability theory.•The ATFSC, fuzzy control, and PI control schemes were experimentally investigated, using the root mean square error (RMSE) performance index to evaluate each scheme.•The robustness of the proposed ATFSC was verified using simulations and experiments, which involved varying parameters and external load disturbances.•The experimental results indicate that the ATFSC scheme outperformed the other control schemes.
This study proposes an adaptive Takagi-Sugeno-Kang-fuzzy (TSK-fuzzy) speed controller (ATFSC) for use in direct torque control (DTC) induction motor (IM) drives to improve their dynamic responses. The proposed controller consists of the TSK-fuzzy controller, which is used to approximate an ideal control law, and a compensated controller, which is constructed to compensate for the difference between the TSK-fuzzy controller and the ideal control law. Parameter variations and external load disturbances were considered during the design phase to ensure the robustness of the proposed scheme. The parameters of the TSK-fuzzy controller were adjusted online based on the adaptive rules derived in Lyapunov stability theory. The ATFSC, fuzzy control, and PI control schemes were experimentally investigated, using the root mean square error (RMSE) performance index to evaluate each scheme. The robustness of the proposed ATFSC was verified using simulations and experiments, which involved varying parameters and external load disturbances. The experimental results indicate that the ATFSC scheme outperformed the other control schemes.
