| 基于RBF神经网络的PID控制在锅炉温度系统中的应用研究 |
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| 引用本文： | 刘悦婷.基于RBF神经网络的PID控制在锅炉温度系统中的应用研究[J].宝鸡文理学院学报(自然科学版),2011,31(2):61-63,68. |
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| 作者姓名： | 刘悦婷 |
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| 作者单位： | 甘肃联合大学电子信息工程学院，甘肃兰州,730000 |
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| 基金项目： | 甘肃省自然科学基金资助(0916RJZA017) |
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| 摘 要： | 目的提高电厂锅炉温度系统控制的可靠性和安全性,达到精确控制。方法提出一种基于RBF(Radial Basis Function)神经网络的PID控制器,建立3层神经网络模型。结果在RBF-PID控制过程中,由神经网络RBF在线辨识得到梯度信息,然后根据梯度信息对PID的3个参数进行在线调整,从而改善系统的控制品质。结论仿真结果表明,基于RBF神经网络的PID控制较传统PID控制有较强的鲁棒性,提高了实时性能,获得了更好的控制效果。
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| 关 键 词： | RBF神经网络 PID控制器 参数整定 锅炉温度系统 仿真 |
Study on boiler temperature system PID control based on RBF neural network |
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| LIU Yue-ting.Study on boiler temperature system PID control based on RBF neural network[J].Journal of Baoji College of Arts and Science(Natural Science Edition),2011,31(2):61-63,68. |
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| Authors: | LIU Yue-ting |
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| Institution: | LIU Yue-ting(School of Electronics and Information Engineering,Gansu Lianhe University,Lanzhou 730000,Gansu,China) |
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| Abstract: | Aim To improve the reliability and security of the temperature control system of boiler in power plant and achieve precise control. Methods PID controller based on RBF(Radial Basis Function)neural network is proposed.Three neural network layers are created. Results Gradient information can be obtained through identification of the RBF neural network on line in the RBF-PID control process and then three PID parameters are set according to the gradient information on line,thus improving the quality of the con... |
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| Keywords: | RBF neural network PID control parameter setting boiler temperature system simulation |
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