| 基于神经网络的开关磁阻电机控制系统研究 |
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| 引用本文： | 于学海,葛宝明. 基于神经网络的开关磁阻电机控制系统研究[J]. 电气传动, 2005, 35(1): 35-38 |
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| 作者姓名： | 于学海 葛宝明 |
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| 作者单位： | 北京交通大学 |
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| 基金项目： | 国家高技术研究发展计划(863计划)，北京交通大学校科研和教改项目 |
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| 摘 要： | 应用神经网络精确建立了SRM的正模型网络与逆模型网络,仿真结果验证了所建模型的正确性和高精度.基于所建模型,提出了有效的SRM转矩脉动最小化控制技术,即以转矩分配函数为基础的期望电流波形控制技术.在期望电流波形控制的基础上,提出了电流滞环控制技术和基于电压模型控制技术,从不同的角度实现了SRM转矩脉动最小化控制,比较了各自的优缺点.
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| 关 键 词： | 开关磁阻电机 转矩脉动最小化 神经网络 |
Research of Switched Reluctance Motor Control System Based on ANNs |
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| Yu Xuehai Ge Baoming. Research of Switched Reluctance Motor Control System Based on ANNs[J]. Electric Drive, 2005, 35(1): 35-38 |
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| Authors: | Yu Xuehai Ge Baoming |
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| Affiliation: | Yu Xuehai Ge Baoming |
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| Abstract: | The ANN-based SRM model whose high precision has been verified by the simulation results is set up. Based on the ANN model of SRM, the effective torque-ripple minimization control techniques are proposed, namely, the desired-current-waveform control technique based on the torque share function. Moreover, the hysteresis band current control and the voltage model control techniques are applied respectively to make the actual current track the desired current, as a result that the torque-ripple minimization is ideally achieved. |
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| Keywords: | SRM torque-tipple minimization artificial neural networks |
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