| 航空发动机多变量神经网络自适应控制仿真研究 |
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| 引用本文： | 孙晓东,李彬,陆宇平.航空发动机多变量神经网络自适应控制仿真研究[J].航天控制,2009,27(6). |
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| 作者姓名： | 孙晓东 李彬 陆宇平 |
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| 作者单位： | 1. 南京航空航天大学自动化学院,南京,210016
2. 山东交通职业学院,潍坊,261000 |
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| 摘 要： | 针对航空发动机是一个具有强非线性、时变不确定性的被控对象,提出了一种基于RBF网络的航空发动机多变量神经网络自适应控制方法,该方法采用RBF网络对发动机非线性模型进行实时辨识,并将系统的灵敏度信息反馈给神经网络控制器,保证了控制器对被控对象的准确控制.通过某涡扇发动机在飞行包线内的数字仿真,结果表明该方法不依赖被控对象的精确模型,有效地实现了对发动机的多变量自适应控制,而且具有较好的动静态性能.
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| 关 键 词： | 航空发动机 RBF网络 神经网络控制器 多变量控制 非线性控制 |
Simulation of Multi-variable Neural Network Adaptive Control for Aeroengine |
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| SUN Xiaodong,LI Bin,LU Yuping.Simulation of Multi-variable Neural Network Adaptive Control for Aeroengine[J].Aerospace Control,2009,27(6). |
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| Authors: | SUN Xiaodong LI Bin LU Yuping |
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| Institution: | SUN Xiaodong1 LI Bin2 LU Yuping11.College of Automation Engineering,Nanjing University of Aeronautics & Astronautics,Nanjing 210016,China2.Shandong Transport Vocational College,Weifang 261000,China |
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| Abstract: | A method of multi-variable neural network adaptive control method based on RBF network is put forward to control aeroengine with strong nonlinearity and time-varying uncertainty. In this method, engine nonlinear model is real-time identified by RBF network, and system sensitivity information is real-time feed back to neural network controller so that the controller can exactly control the engine. Through digital simulation of some turbofan engine in the full flight envelope, the results show the proposed method does not depend on the aeroengine precise model, it can effectively realize the multi-variable control for aeroengine, and the controlled plant has good dynamic and static performances. |
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| Keywords: | Aeroengine RBF network Neural network controller Multi-variable control Nonlinear control |
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