| 基于小波神经网络的蒸汽发生器水位辨识与控制仿真 |
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| 引用本文： | 陈登科,张大发.基于小波神经网络的蒸汽发生器水位辨识与控制仿真[J].海军工程大学学报,2006,18(6):102-105. |
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| 作者姓名： | 陈登科 张大发 |
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| 作者单位： | 海军工程大学,船舶与动力学院,湖北,武汉,430033 |
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| 摘 要： | 提出一种基于小波神经网络的控制方法,对蒸汽发生器水位进行控制仿真.该方法利用小波神经网络作为控制系统的辨识器和控制器来构成控制系统.小波神经网络辨识器能更准确逼近非线性对象,小波神经网络控制器能自适应产生最佳的控制规律.仿真结果表明,该方案具有响应快、超调量小、较强抑制干扰能力等良好性能.
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| 关 键 词： | 小波神经网络 辨识 自适应 蒸汽发生器 水位控制 |
| 文章编号： | 1009-3486(2006)06-0102-04 |
| 修稿时间： | 2006年4月3日 |
A simulation of identification and control for steam generator water level based on wavelet neural network |
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| CHEN Deng-ke,ZHANG Da-fa.A simulation of identification and control for steam generator water level based on wavelet neural network[J].Journal of Naval University of Engineering,2006,18(6):102-105. |
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| Authors: | CHEN Deng-ke ZHANG Da-fa |
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| Abstract: | A control method can hardly meet the requirement.The control system based on wavelet neural network is proposed.This system consisting of a wavelet neural network controller and a wavelet neural network identifier can identify nonlinear system dynamic characters more precisely,and can adapt to better control strategies.The simulation results show that this scheme is characterized by rapid response,small overshoots and strong anti-interfering power. |
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| Keywords: | wavelet neural network identification adaptive steam generator water level control |
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