새로운 직접토크제어에 의한 유도전동기의 센서리스 속도제어
A Study on the Sensorless Speed Control of Induction Motor by New Direct Torque Control
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초록
본 논문은 신경회로망 기법을 이용하여 직접벡터제어 방식의 문제점을 개선하고자 하였다. 직접벡터제어 방식은 히스테리시스 밴드 폭의 변화로 인해 유도전동기 속도제어 시 맥동이 큰 단점을 가지고있다. 이러한 문제점을 학습을 통해 오차를 감소시키는 신경회로망 기법을 사용하여 기존의 직접벡터제어 방식에서 발생하던 속도 맥동을 개선하였다.
Abstract
This paper presents an improved direct torque control based on artificial neural networks technique. The major problem that is usually associated with DTC drive is the high torque(speed) ripple. To overcome this problem a torque hysteresis band with variable amplitude is proposed based on artificial neural networks. The artificial neural networks proposed controller is shown to be able to reducing the torque(speed) ripple and dependency on motor parameter and to improve performance DTC especially at high speed and reversal running.
참고문헌 (7)
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- Chengzhi Cao, "Speed estimation and stimulation of dtc system based on wavelet neural network", Proceedings of the Second International Conference on Machine Leaning and Cybernetics, 통권 : Xi, pp.755~759 (2003)