| RBF和PIDNN在伺服电机模型中的应用比较 |
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| 引用本文： | 董伟杰,刘长华,宋华. RBF和PIDNN在伺服电机模型中的应用比较[J]. 控制工程, 2008, 0(Z1) |
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| 作者姓名： | 董伟杰 刘长华 宋华 |
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| 作者单位： | 北京航空航天大学自动化学院，中国民用航空飞行学院广汉分院 |
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| 摘 要： | 为了更好地发挥RBF和PIDNN神经网络的优势,通过对伺服电机模型辨识和控制问题的分析,对RBF和PIDNN网络的应用效果进行了仿真实验的对比研究。结果表明,RBF神经网络结构复杂,参数难以调整,但具有最佳一致逼近能力,辨识效果优于PIDNN;PIDNN结构简单,比例元、积分元和微分元具有类似PID的控制作用,控制效果优于RBF。
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| 关 键 词： | 径向基神经网络 PID神经元网络 伺服电机 系统辨识 神经网络控制 |
Application Contrast on Servo Electromotor Model between RBF and PIDNN |
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| DONG Wei-jie,LIU Chang-hua,SONG Hua. Application Contrast on Servo Electromotor Model between RBF and PIDNN[J]. Control Engineering of China, 2008, 0(Z1) |
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| Authors: | DONG Wei-jie LIU Chang-hua SONG Hua |
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| Affiliation: | DONG Wei-jie1,LIU Chang-hua2,SONG Hua1 |
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| Abstract: | To take the advantages of RBFNN and PIDNN,the simulations and contrast research of their application effect are done by analyzing model inentification and control problems of servo electromotor.The experimet results show that RBF network has complex structure and its parameters are difficult to adjust.But the RBFNN has an ability of optimal coherent approach,so its identification effect is better than the PIDNN.PIDNN has simple PID-function-bearing structure of proportion cell,integral cell and differential cell,so its control effect is better than RBFNN. |
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| Keywords: | RBF PIDNN servo electromotor system identification neural networks control |
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