基于量子遗传算法的无人机冲突解脱方法

飞行冲突解脱对于无人机飞行安全至关重要,遗传算法(genetic algorithm, GA)在解决无人机冲突解脱时存在求解速度慢、产生的延误距离较大等缺点,针对这些缺点,提出一种基于量子遗传算法(quantum genetic algorithm, QGA)的无人机冲突解脱方法。该方法采用了量子比特编码,设计加入了延误指数函数强制优化策略和变航向优化策略,通过利用量子旋转门实现个体的演化,并在延误距离、冲突解脱航迹等多方面与遗传算法进行了对比实验。仿真实验结果表明,该方法与遗传算法相比,求解速度更快,解的质量更高,所得解脱航迹更平滑,能获得较小的飞行延误,在无人机冲突解脱方面具有有效性和良好的应用价值。

A Method of UAVs Conflict Resolution Based on Quantum Genetic Algorithm

Flight conflict resolution is very important for UAVs flight safety. Genetic algorithm(GA) has some shortcomings in solving UAVs conflict resolution. For example, GA has slow solution speed and causes large delay distance. Aiming at these shortcomings, a method of UAVs conflict resolution based on quantum genetic algorithm(QGA) was proposed in this paper, which adopted the qubits coding and designed the forced optimization strategy of delay exponential function and course-changing optimization strategy. The quantum rotation gate was used to realize the evolution of the individuals. The proposed method was compared with GA in many aspects, such as delay distance, conflict resolution tracks and so on. The simulation results show that compared with GA, the proposed method has faster solution speed, higher solution quality, smoother conflict resolution tracks and less flight delay. So the proposed method has good effectiveness and application value in UAV conflict resolution.