| 基于蚁群模糊神经网络的无刷直流电机仿真控制研究 |
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| 引用本文： | 乔维德. 基于蚁群模糊神经网络的无刷直流电机仿真控制研究[J]. 电气传动自动化, 2009, 31(5): 6-10 |
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| 作者姓名： | 乔维德 |
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| 作者单位： | 常州市广播电视大学,江苏,常州,213001 |
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| 摘 要： | 无刷直流电机（BLDCM）的动力学特性是一个高阶、非线性、强耦合的系统，针对传统PI控制的滞后性和动态响应性能较差等特点，提出一种基于动态递归模糊神经网络PI控制的无刷直流电机调速系统速度控制器的实施方案，利用蚁群算法优化递归模糊神经网络的隶属度函数参数和网络权值系数，从而提高系统的动态响应性能。仿真结果表明，该方法响应快，具有较强的抗干扰性和鲁棒性，动、静态特性均优于传统PI控制。
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| 关 键 词： | 无刷直流电机(BLDCM) 模糊神经网络 PI控制 蚁群算法 |
Research on simulation control of brushless DC motor based on ant colony fuzzy neural network |
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| QIAO Wei-de. Research on simulation control of brushless DC motor based on ant colony fuzzy neural network[J]. Electrical Drive Automation, 2009, 31(5): 6-10 |
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| Authors: | QIAO Wei-de |
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| Affiliation: | QIAO Wei-de(Changzhou Television & Radio University,Changzhou 213001,China) |
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| Abstract: | The dynamic characteristics of brushless DC motor(BLDCM)is a high-order,nonlinear and strong coupling system.According to the lagging and the dynamic poor response,a method of dynamic PI control to the speed system of BLDCM is presented.Using ant colony algorithm to optimize the membership function parameters and the network coefficient of recurrent fuzzy neural network,thereby improve the dynamic performance.The simulation results show that the method has fast response,strong coupling and robustness,and th... |
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| Keywords: | brushless DC moto(rBLDCM) fuzzy neural networks PI control ant colony algorithm |
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