将一种改进了的BP神经网络算法应用于飞机压力加油系统容错控制中,进行了仿真和实验,并对仿真结果进行了分析,仿真结果表明,加入BP算法以后的压力加油控制律大大缩短了加油时间,并且提高了压力加油的控制精度,此项研究为开发基于神经网络的飞机燃油故障诊断专家系统奠定基础。 An improved BP neural network algorithm is applied to the fault-tolerant control of aircraft pressure refueling system, and the simulation and experiment are carried out. The simulation results are also analyzed. The simulation results show that the pressure refueling control law after the addition of BP algorithm is greatly reduced Fueling time, and improve the control accuracy of pressure and fuel. This study lays the foundation for the development of an expert system for aircraft fuel fault diagnosis based on neural network.