| Summary: | 碩士 === 國立臺北科技大學 === 機電整合研究所 === 92 === In this thesis, based on the grey theory, a grey prediction controller is designed with fuzzy step prediction to improve the dynamic performance of the considered system. Since the fuzzy prediction step size is dynamically regulated, the disadvantage of the conventional fixed-step-size grey prediction controller is overcome and the system dynamic response can be improved. To verify the performance of the proposed controller, the grey prediction controller is implemented in the induction motor control system.
The considered control scheme is direct torque control (DTC) because the advantages of the direct torque control system include low computation complexity, simple construction, and quick dynamic response. However, the conventional hysteresis direct torque control encounters the torque ripple and noise problems. To solve the problem, the space vector modulation (SVM) is used to reduce torque ripple caused by the inadequate selection of bandwidth of hysteresis.
From the experimental results, while the motor speed changes from 150 rpm to 1800 rpm with 8 Nm load, it is seen that the performance of the grey prediction controller is superior, the dynamic response is obviously improved, and the precision control of induction motor is achieved.
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