Application of Neural Network to Torque Identification of Torpedo AC Motor
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摘要: 针对采用传统转矩控制方法不能建立精确的数学模型,而难以满足系统性能要求,为提高鱼雷异步电机在线参数识别的效率和可靠性, 提出了一种基于BP神经网络的鱼雷交流电机转矩辨识方法。通过假设推算出电机转矩表达式,利用基于BP神经网络进行转矩辨识,该方法不需要辨识对象的数学模型,只需对神经网络进行在线或离线训练,利用训练结果便可进行辨识系统设计。仿真结果表明,该辨识方法能够取得较好的辨识精度。Abstract: Because the conventional torque control method can not be used to build up an accurate mathematical model,in order to improve the efficiency and reliability of online parameter identification for torpedo asynchronous motor,a method for identifying the torque of a torpedo AC motor based on back propagation (BP) neural network is presented to meet the requirement of system performance. An equation of AC motor torque is derived on hypothesis,and the torque is identified by the BP neural network trained online or offline, without the need for a mathematical model of target.The training results are used to design the identifying system.The simulation results show better accuracy of the torque identification with the proposed method.
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Key words:
- neural network /
- torpedo /
- AC motor /
- torque identification
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