| 基于改进遗传RBF神经网络的双电机驱动伺服系统控制 |
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| 引用本文： | 赵海波.基于改进遗传RBF神经网络的双电机驱动伺服系统控制[J].井冈山大学学报（自然科学版）,2011(4):76-80. |
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| 作者姓名： | 赵海波 |
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| 作者单位： | 光电子应用安徽省工程技术研究中心;铜陵学院电气工程系; |
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| 基金项目： | 安徽省高校自然科学研究项目(KJ2011B186) |
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| 摘 要： | 针对常规遗传算法的缺陷,提出了一种基于改进遗传算法和RBF神经网络相结合的控制方法.该方法对RBF神经网络的隐层中心值和宽度进行了优化,用递推最小二乘法训练隐层和输出层之间的权值.最后在双电机驱动伺服系统中进行了仿真试验,结果表明所提出的控制策略是有效的.
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| 关 键 词： | 遗传算法 RBF神经网络 双电机驱动 |
CONTROL OF DUAL-MOTOR DRIVING SERVO SYSTEM BASED ON IMPROVED GENETIC-RBF NEURAL NETWORK |
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| ZHAO Hai-bo.CONTROL OF DUAL-MOTOR DRIVING SERVO SYSTEM BASED ON IMPROVED GENETIC-RBF NEURAL NETWORK[J].Journal of Jinggangshan University(Natural Sciences Edition),2011(4):76-80. |
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| Authors: | ZHAO Hai-bo |
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| Institution: | ZHAO Hai-bo1,2(1.Engineering Technology Reaearch Center of Optoelectronic Appliance,Anhui Province,Tongling Anhui,244000,China,2.Department of Electrical Engineering,Tongling University,China) |
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| Abstract: | According to the deficiency of conventional genetic algorithm(GA),a new control method based on improved GA which combining with RBF neural network is proposed.The method was used to optimize the centers and widths of RBF hidden layer.Recursion least square method was used to train the weights between hidden layer and output layer.Finally,the simulation experiment in dual-motor driving servo system shows the effectiveness of the proposed control strategy. |
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| Keywords: | genetic algorithm RBF neural network dual-motor driving |
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