| 航空发动机神经网络反步控制方法 |
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| 引用本文： | 潘慕绚,黄金泉,殷石.航空发动机神经网络反步控制方法[J].航空动力学报,2009,24(10):2344-2348. |
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| 作者姓名： | 潘慕绚 黄金泉 殷石 |
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| 作者单位： | |
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| 摘 要： | 针对航空发动机非线性和不确定性的特点,提出了一种基于神经网络的反步控制方法.采用径向基神经网络估计未知系统方程,并用一种平滑切换法有效避免了控制器奇异问题.反步法的设计基于Lya-punov稳定性原理,保证了闭环系统一致渐近有界.最后针对某型涡扇发动机非线性模型设计了高压转速控制器,仿真结果验证了该方法的有效性.
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| 关 键 词： | 航空发动机 非线性系统 神经网络 反步控制 |
| 收稿时间： | 2008/10/9 0:00:00 |
| 修稿时间： | 3/24/2009 1:36:24 PM |
Backstepping control strategy for aero-engine using neural networks |
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| PAN Mu-xuan,HUANG Jin-quan and YIN Shi.Backstepping control strategy for aero-engine using neural networks[J].Journal of Aerospace Power,2009,24(10):2344-2348. |
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| Authors: | PAN Mu-xuan HUANG Jin-quan and YIN Shi |
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| Institution: | College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China |
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| Abstract: | Abstract: A Backstepping control strategy based on neural network is presented for nonlinearity and uncertainty of aeroengine. RBF neural network is used to estimate the equations of the unknown system, and a smooth-switching algorithm is proposed to avoid singularity phenomenon. Using Lyapunov stability analysis, the uniformly ultimately boundedness of closed-loop systems is proven.Finally ,the compressor speed controller is designed based on a nonlinear model of some turbofan engine. The simulation results illustrate the effectiveness of the proposed approach. |
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| Keywords: | aerospace propulsion system aeroengine nonlinear system neural network backstepping control |
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