An adaptive Takagi-Sugeno-Kang fuzzy speed controller design for the direct torque control system of induction motors

Based on the Takagi-Sugeno-Kang (TSK) fuzzy controller and adaptive control theory, this study presents the design of an adaptive TSK fuzzy controller (ATSKFC). With an online learning function, this controller is an improvement on the traditional PI controller, whose parameters are fixed. An improved model for a compensating controller is also proposed to address the problems caused by the fixed parameters of traditional compensating controllers, and thereby enhance the transient responses of motors. Because the stator resistance of induction motors varies according to changes in temperature, this study designed a MRAS stator resistance estimator based on the model reference adaptive system (MRAS) and ATSKFC to enable real-time adjustments of the stator resistance. By adopting direct torque control (DTC) technology, this study was able to control the induction motor speed and thereby obtain various benefits, such as fast transient responses, a simple architecture, and simple computing processes. To solve torque ripple and noise problems caused by conventional hysteresis torque and flux control, this study employed the space voltage vector modulation technique for DTC. Additionally, we used a speed estimator to realize speed sensor-free control, with the benefits of lowering costs and preventing damage to the motor structure.