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基于自适应人工神经网络的无刷直流电机换相转矩波动抑制新方法
引用本文:夏长亮,文德,王娟.基于自适应人工神经网络的无刷直流电机换相转矩波动抑制新方法[J].中国电机工程学报,2002,22(1):54-58.
作者姓名:夏长亮  文德  王娟
作者单位:天津大学电气自动化与能源工程学院,天津,300072
基金项目:天津市自然科学基金重点资助项目 ( 0 1380 0 811)
摘    要:分析了无刷直流电机换相转矩波动产生原理,提出了基于自适应人工神经网络控制的转矩波动抑制新方法,该方法对两个三层前馈式人工神经网络进行离线和在线训练,采用误差反传算法修正神经元间的权值。其中一个网络用于在线估计电机换相参数,另一个网络利用估计出的参数对换相过程中端电压瞬时调节,形成一个电压自校正调节器。该调节器通过调节端电压使换相过程中相电流下降和上升的速率近似相等,保持回路中总电流幅值不变,实现对换相转矩波动的抑制,该方法不需预知系统的精确参数,且对环境变化有自适应调节功能,试验结果表明该方法有较高的精度和鲁棒性。

关 键 词:无刷直流电机  换相  转矩波动  自适应人工神经网络
文章编号:0258-8013(2002)01-0054-05
修稿时间:2001年7月26日

A NEW APPROACH OF MINIMIZING COMMUTATION TORQUE RIPPLE FOR BRUSHLESS DC MOTOR BASED ON ADAPTIVE ANN
XIA Chang liang,WEN De,WANG Juan.A NEW APPROACH OF MINIMIZING COMMUTATION TORQUE RIPPLE FOR BRUSHLESS DC MOTOR BASED ON ADAPTIVE ANN[J].Proceedings of the CSEE,2002,22(1):54-58.
Authors:XIA Chang liang  WEN De  WANG Juan
Abstract:In this paper, the principle of commutation torque ripple (CTR) for brushless DC motor is analyzed, and a new approach of minimizing CTR is presented, which is based on adaptive artificial neural network (ANN) control.Two three layer forward artificial neural networks are trained both in off line and in on line ways, and the weights in networks are updated using the error back propagation (BP) algorithm. One of the networks is used to estimate the commutation parameters of the motor online. The other is used to regulate the terminal voltages using the parameters estimated by the former network during commutation. In this way, the whole model can be considered as a voltage self tuning regulator (STR). Through regulating the terminal voltages of motor, the STR makes the rising ratio and dropping ratio of the phase currents be approximate in order to keep the amplitude of the total current in the circuit constant, so as to minimize CTR. This approach is unnecessary to know the accurate system parameters, and can modify the model adaptively while parameters are changed. The experimental results show that the proposed method is highly precise and robust.
Keywords:brushless DC motor  torque ripple  artificial neural network
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