基于自适应遗传算法的客机爬升段轨迹优化

Climb Trajectory Optimization of Aircraft based on Adaptive Genetic Algorithm

研究民航客机爬升段轨迹优化问题。由于单独节省时间或节省燃油问题,均存在互相影响。为了让客机能够在舒适和省油的前提下尽快爬升到巡航高度,综合考虑了时间和燃料消耗两项优化指标。首先,结合客机爬升阶段的运动方程和性能指标,以及民航飞行规章给出了爬升段轨迹的优化模型;其次,为提高基因的多样性和算法的收敛速度,对自适应遗传算法进行相应改进,使其更适用于客机爬升段轨迹优化;最后,根据民航客机航迹规划要求,给出了具体的优化步骤,并以波音747-200为实例进行爬升段飞行轨迹优化仿真验证。仿真结果表明,改进方法能在满足全部约束条件下最优化性能指标,并能快速收敛,可靠地规划出爬升段最优飞行轨迹。

The trajectory optimization of the civil aviation aircraft is studied. In order to allow the aircraft to climb to the cruising altitude under the premise of comfort and fuel economy as soon as possible, two optimization indexes of time and fuel consumption are considered. Firstly, the trajectory optimization model of aircraft during climbing by combining motion equations, performance index, and civil aviation flight rules. Secondly, in order to improve the genetic diversity and the algorithm convergence speed, the adaptive genetic algorithm is improved to make it more appropriate to climb trajectory optimization. Finally, according to the requirements of civil aviation aircraft route planning, some specific optimization steps are put forward. Taking Boeing 747-200 as an example, the climb trajectory optimization is simulated. The simulation results show that the method satisfies the performance index and the optimal flight trajectory with quick convergence.