军用飞机斤斗类飞行轨迹最优化方法

针对军用飞机斤斗类飞行过程,以半滚倒转和半斤斗翻转为例,建立机动飞行计算模型。根据最小机动速度设置改出速度约束条件,将斤斗类机动平均分段,利用神经网络的拟合功能,得到动作改出速度和操纵条件之间的非线性关系。利用遗传算法的全局寻优功能,结合神经网络得到的权重和偏置结果,探索机动过程中边界飞行性能最大的法向过载选取方法。仿真结果表明,与相关手册中给出的常规操纵方法相比,利用遗传算法优化后得到的过载控制规律飞行,可以使飞机具有更大的高度-速度范围,同时,比直接将遗传算法和数值积分相结合具有更快的计算速度。提出的方法也可以用于其他机型斤斗类飞行轨迹的最优化设计中。研究结果具有一定的实用价值。

Optimizing Method for Flight Trajectory of Military Aircraft Loop-type maneuver

In view of the loop-type flight process of military aircraft, the computational model of maneuvering flight was established by taking split-s and immelman as examples. According to the minimum maneuvering speed setting, the speed constraint condition was set. The average maneuvering segment of the bucket was divided. By using the fitting function of the neural network, the non-linear relationship between the maneuvering speed and the maneuvering condition was obtained. By using the global optimization function of genetic algorithm and combining the weights and bias results obtained by neural network, the overload selection method for maximizing boundary flight performance in maneuvering process was explored. The simulation results show that the overload control law flight obtained by genetic algorithm optimization can make the aircraft have a larger altitude-velocity range than the conventional control method given in the relevant manual. At the same time, the method in this paper is faster than that of combining genetic algorithm with numerical integration directly. The proposed method can also be used in the optimization design of flight trajectories of other types of aircraft loop-type and has certain practical value.