飞行器神经元控制系统的研究与设计

 提出了一种基于神经元网络的飞行控制系统设计方法 ,该方法设计的神经元飞行控制器具有良好的鲁棒性 ,使飞行器在整个飞行包络内都能保持某种最优的操纵品质。给出的计算机仿真结果显示出神经元网络作为飞行控制器在处理飞行器参数大范围变化的非线性特性方面具有潜在的优良品质

STUDY AND DESIGN OF A FLIGHT NEUROCONTROL SYSTEM

A design method of flight control systems with neural networks is presented,by which the designed flight neurocontrol system possesses a strong robustness and can achieve the ideal system performance. The controlled flight system has a nonlinear state feedback configuration and an optimal system performance specification. A self learning optimal control algorithm is proposed to solve the optimal control problem and get training samples of the optimal control law, and an improved backpropagation algorithm is employed to train the neurocontroller in the whole flight envelope. The method is implemented into a fighter nonlinear simulation. By self learning and being trained, the fighter controlled by the neurocontroller has achieved the optimal system performance in the whole flight envelope. The simulation results show that neural networks used as flight controllers are full of promise.