Speed Sensorless Control System of Induction Machine Using Adaptive Rotor Resistance Observer
Due to quick torque response and robustness against parameter variation, the direct torque control system has been widely utilized in the industrial production. To improve its dynamic performance, a novel approach using wavelet network for identifying stator resistance on-line is proposed. The wavelet transform can accurately detect and localize signal characteristic in time-frequency domains, where the real-time stator resistance variation can be tracked. The wavelet network provides a sufficient structure that guarantees the approximation precision. Comparing with neural network, the wavelet network has four merits: self-construction network, partial retrieval of approximated function, fast convergence and escaping local minima, improving dynamic performance of direct torque control in low speed. The input nodes of wavelet network have two variables: one is stator current error, and the other is variance ratio of stator current error. The output node of wavelet network is stator resistance error. The improved least squares algorithm is used to complete the network parameter initialization, which would have good convergence property. The simulation results prove that the proposed method can efficiently reduce the torque ripple and current ripple, optimizing the inverter control strategy.
Induction motor dynamic performance wavelet network stator current stator identification parameter initialization low speed
Kang Shanlin Kang Yuzhe Zhang Huanzhen
Hebei University of Engineering, Handan 056038, China Beijing University of Chemical Technology, Beijing 100029, China
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
286-289
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）