| Summary: | 碩士 === 國立臺北科技大學 === 電機工程系研究所 === 97 === In this thesis, the adaptive TSK fuzzy controller (ATSKFC) is proposed, which is designed using the TSK fuzzy controller and adaptive control theory. This controller has on-line learning ability to overcome the drawbacks of the traditional parameter-fixed PI controller. Moreover, the TSKFC with an auxiliary compensator is capable of offering more flexible compensation effort to improve transient responses for the induction motor. Due to the variation of stator resistance of induction motor caused by temperature change, the MRAS stator resistance estimator is designed to real-time estimate stator resistance based on the model reference adaptive system (MRAS) with adaptive TSK fuzzy controller.
The ATSKFC speed controller and the MRAS stator resistance estimator are both implemented on DTC induction motor drives to gain the classic merits of DTC, including simple structure, fast system responses and low computation complexity. In order to solve the problems of torque ripple and noise caused by the conventional DTC scheme, the space vector pulse width modulation (SVPWM) technique is chosen in this research. In addition, the speed estimator is utilized to realize the speed sensorless control to achieve the advantages of cost-effectiveness and structure robustness.
From the experimental results, it is observed that the excellent tracking performance is achieved by using the proposed approach with 8 Nm torque load, under the speed operational range from 36 rpm to 2000 rpm. Furthermore, the stator resistance can be estimated accurately by the proposed MRAS stator resistance estimator.
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