Design of Adaptive Takagi-Sugeno-Kang Fuzzy Estimators for Induction Motor Direct Torque Control Systems

By referencing the adaptive stator flux estimator (ASFE) framework in the model reference adaptive system (MRAS), this study designed an adaptive rotor speed estimator and a stator resistance estimator, and applied the Takagi-Sugeno-Kang (TSK) fuzzy system and projection algorithms to the estimators to establish an induction motor direct torque controlled system without a speed sensor and possessing stator resistance adjustment abilities. In addition, the adaptive TSK fuzzy controller (ATSKFC) was adopted as the speed controller of the system, and was capable of online learning. The transient response was improved by the integration of a refined compensation controller. Induction motor controlled drive system was implemented in this study by using direct torque control (DTC) technology, which had the advantages of a rapid dynamic response, simple system structure, and low computational complexity. In addition, the application of the voltage space vector pulse width modulation (VSVPWM) technique reduced the torque ripples and noise, which are common in a traditional DTC system. The simulation and experimental results demonstrated that, with the proposed adaptive TSK fuzzy rotor speed estimator (ATSKFRSE), adaptive TSK fuzzy stator resistance estimator (ATSKFSRE), and an ATSKFC implanted into the induction motor DTC system, the system provided an excellent speed dynamic response and was able to estimate the rotor speed and stator resistance accurately at an 8-Nm load torque and a wide speed range of 36-2000 rpm.