基于神经网络的超机动飞机自适应重构控制

 讨论了一种基于神经网络的超机动飞机直接自适应重构控制方法。飞机的基本控制律采用非线性动态逆方法设计,对于模型不准确和舵面故障等因素导致的逆误差采用神经网络进行在线补偿。通过仿真表明,在飞机发生舵面故障时,神经网络通过自适应地补偿逆误差,可以快速在线重构控制律,保持飞机稳定和一定的操纵品质。

Neural-Net Based Adaptive Reconfigurable Control for a Super-Maneuverable Aircraft

This paper describes a neural network based direct adaptive control approach to the problem of reconfigurable flight control of a super-maneuvering aircraft. The base control law is designed in nonlinear dynamic inversion, and neural networks are used to cancel the inversion error induced by many reasons, especially by actuator failures. Simulation of two types of actuator failures show that through adaptively canceling the inversion error, neural networks can reconfigure the control instantly when there should be actuator failures. The system will keep steady and maintain certain handling qualities.