无人飞行器纵向剖面轨迹优化

Optimization of vertical profile trajectory for unmanned aerial vehicle

对飞行管理系统的纵向剖面轨迹优化功能进行了研究.以固定距离最省油为优化指标,用能量法动态地建立了3阶段轨迹优化模型.区别于固定推力只对速度寻优的传统的模型求解方法,把发动机推力和速度同时作为寻优变量,并结合无人飞行器飞行的物理过程,将3阶段轨迹优化模型进一步变换成非线性规划问题,利用再开始FR(Fletcher-Revees)共轭梯度法进行求解.最后以某型无人飞行器为例进行仿真验证,结果表明将发动机推力设为变量比推力固定求得的纵向剖面最优轨迹更省油,对节省燃油降低经济成本有一定的实用参考价值.

In optimizing the vertical profile trajectory by energy method, we choose the fuel-efficient performance index for a given distance as the cost function and build a three-stage trajectory-optimization model. Being different from traditional methods that optimize the speed, while keeping the engine thrust in constant, this method optimizes both the engine thrust and the speed simultaneously. The three-stage trajectory-optimization model combined with the real flight process of the unmanned aerial vehicle is transformed into a nonlinear programming problem to be solved by using the restart FR （Fletcher-Revees） conjugate gradient method. Simulations have been carded out on the unmanned aerial vehicle model. Results show that vertical profile optimal trajectory obtained by the proposed algorithm saves more fuel than that obtained by keeping the engine thrust in constant. The superiority in fuel-saving and cost-reduction is significant.