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| Application of Neural Network in Penetration of Air-breathing Hypersonic Missile |
| Wei Liming，Li Xiaolong, Zhao Zheng, Du Sha, Wang Jiuzhou |
| Shanghai Electro-Mechanical Engineering Institute, Shanghai 201109, China |
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Abstract The neural network is trained for the maneuvering of airbreathing hypersonic missile at extreme overload in the longitudinal plane, based on a large number of dichotomies simulation data; considering the dynamic pressure window and the attack angle window; setting the missile maneuvering initial height, Mach number and mass as neural network inputs, and the maximum value of the maneuvering time that the missile maneuvering with the extreme overload as neural network output. The trained neural network can predict the maximum maneuver time by the initial conditions. On the basis, longitudinal maneuvering penetration method is designed by setting the maximum value of the maneuvering time as the upper bound and random selecting the time that the missile maneuvering with the extreme overload. The feasibility of this method is verified by simulation.
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Received: 29 December 2017
Published: 09 April 2018
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2018, Vol. 1 
