| 航空发动机小波神经网络PID控制 |
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| 引用本文： | 李秋红,许光华,孙健国. 航空发动机小波神经网络PID控制[J]. 航空动力学报, 2009, 24(4): 875-879 |
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| 作者姓名： | 李秋红 许光华 孙健国 |
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| 作者单位： | 南京航空航天大学,能源与动力学院,南京,210016;南京航空航天大学,能源与动力学院,南京,210016;南京航空航天大学,能源与动力学院,南京,210016 |
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| 摘 要： | 提出了一种基于小波神经网络在线辨识的航空发动机比例-积分-微分(PID)控制算法.网络采用三层前向网络结构,以小波函数作为隐含层的激励函数.采用离线训练的方式训练出网络参数,以网络输出和输入之间的偏导数代替发动机模型输出和输入变量之间的偏导数,用以在线修正PID控制器的参数.阶跃响应测试表明,用小波神经网络整定的PID控制系统动态调节时间小于2s,稳态误差为零,在全飞行包线内均稳定正常工作.
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| 关 键 词： | 比例-积分-微分(PID)控制 航空发动机 小波 神经网络 |
| 收稿时间： | 2008-03-20 |
| 修稿时间： | 2008-08-21 |
Aero-engine wavelet neural network PID control |
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| LI Qiu-hong,XU Guang-hua and SUN Jian-guo. Aero-engine wavelet neural network PID control[J]. Journal of Aerospace Power, 2009, 24(4): 875-879 |
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| Authors: | LI Qiu-hong XU Guang-hua SUN Jian-guo |
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| Affiliation: | College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China |
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| Abstract: | An aero-engine proportion integration differentiation(PID) control method based on wavelet neural network on-line identification was proposed in this paper.The network structure was available with a three layers feed-forward neural network.The wavelet function was used as the activation function of the network's hidden layer.The network parameters were trained off-line.The derivative of the network's output to input was used as the engine model's derivative,and it was used to adjust the PID parameters on-li... |
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| Keywords: | proportion integration differentiation(PID) aero-engine wavelet neural network |
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