风影响下航空器多目标最优控制航迹优化方法

A multi-objective optimal control trajectory optimization method for aircraft under wind influence

风影响下的四维航迹优化问题约束复杂,多目标四维航迹优化模型难以求解。基于最优控制方法研究固定水平航路下考虑风影响的航迹垂直剖面多目标优化问题的建模和求解。以飞行时间和飞行油耗最小化为双目标建立航迹最优控制模型;设计了梯形配点结合ε-约束方法的模型求解方法,并针对按高度层飞行场景下的航迹优化提出两阶段求解方法;建立了四维航迹仿真模型用于对轨迹优化效果的仿真验证;选用长航线实际飞行计划数据作为算例进行算法性能分析,并区分自由高度飞行和按高度层飞行2种场景进行航迹优化效果验证。实验结果表明:所提模型和所提方法相比其他2种常用算法能获得更优的Pareto前沿解,按高度层飞行场景下采用所提方法能获得更优的前沿解;自由高度飞行和按高度层飞行2种场景下求得的前沿解中最小燃油耗航迹分别比飞行计划仿真航迹的油耗降低了6.33%和5.94%,最短飞行时间航迹分别比飞行计划仿真航迹的飞行时间降低了10.16%和10.01%。

The constraints of the 4D trajectory optimization problem under wind influence are complex,and the multi-objective 4D trajectory optimization model is difficult to solve.To this end,the modeling and solution of the multi-objective optimization problem of the vertical profile of the trajectory under a fixed horizontal flight path considering wind influence were studied based on the optimal control method.Firstly,the optimal trajectory control model was established with the objectives of minimizing flight time and flight fuel consumption.Then,a modelε-constraintsolution method combining trapezoidal points with was designed,and a two-stage solution method was proposed especially for trajectory optimization under the flight scenario by altitude layer.Then,a 4D trajectory simulation model was established to verify the effect of trajectory optimization.Finally,the actual flight plan data of the long flight route was used as an example to analyze the performance of the algorithm,and two scenarios of flight at free altitude and flight by altitude layer were used to verify the effect of trajectory optimization.The experimental results show that the proposed model and algorithm can obtain better Pareto frontier solutions than the other two commonly used algorithms,and the two-stage solution method can obtain better frontier solutions in the flight scenario by altitude layer.In the frontier solutions obtained in the scenarios of flight at free altitude and flight by altitude layer,the lowest flight fuel consumption trajectories are reduced by 6.33%and 5.94%,respectively,compared with those of the flight plan simulation trajectories.The shortest flight time trajectory is 10.16%and 10.01%lower than that of the flight plan simulation trajectory.