Volume 35 Issue 4
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YAN Zhaohong, QIU Xiaojie, HUANG Jinquan. Neural network control of aircraft engine thrust ,degradation mitigation[J]. Journal of Aerospace Power, 2020, 35(4): 844-854. doi: 10.13224/j.cnki.jasp.2020.04.018
Citation: YAN Zhaohong, QIU Xiaojie, HUANG Jinquan. Neural network control of aircraft engine thrust ,degradation mitigation[J]. Journal of Aerospace Power, 2020, 35(4): 844-854. doi: 10.13224/j.cnki.jasp.2020.04.018
shu

Neural network control of aircraft engine thrust ,degradation mitigation

doi: 10.13224/j.cnki.jasp.2020.04.018
  • 1.

    Jiangsu Province Key Laboratory of Aerospace Power System,College of Energy and Power Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China

  • 2.

    Aero Engine Control System Institute,Aero Engine Corporation of China,Wuxi Jiangsu 214063,China

  • Received Date: 2019-08-05
  • Publish Date: 2020-04-28
    Abstract
  • A thrust degradation mitigation neural network control method of aircraft engine was proposed based on variable incremental linear programming (LP) optimization, due to performance deterioration of the gas path components. This method alleviated the engine thrust degeneration through control of high-pressure rotor speed and the engine pressure ratio by the inner loop, and correction of the engine command signal by the outer loop. The inner loop nonlinear autoregressive moving average (NARMA-L2) speed controller was obtained by neural network, and the outer command correction loop used the variable incremental LP optimization method to adjust the engine command signal. Simulations on a low-bypass-ratio-turbofan engine were performed. Results showed that under the 4 sets of simulation conditions, the designed control method can mitigate the thrust at least 46.5%, ensuring that the engine with performance deterioration was not overrun. The effectiveness of the method has been verified.

     

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