基于混沌遗传算法的航迹优化研究*

在实际作战环境中,如何选择最优的航迹路线是无人机任务规划系统中最重要的问题之一。首先,在有效巡查区域中建立以总路程最少和时间均衡度最小的双目标航迹优化模型,然后提出一种基于混沌遗传算法的航迹规划;该算法利用Logistic混沌序列确定遗传算法交叉和变异点,保证了算法收敛精度,削弱了因交叉强度大而产生的抖振问题,并将该算法应用到了航空规划问题上进行实验仿真,仿真结果表明该方法提高了遗传算法的精确度。

Track Optimization Based on Chaos Genetic Algorithm

How to choose the optimal trajectory is one of the most important problems in the UAV mission planning system when the UAV is applied to actual combat environment. In this dissertation, a two target trajectory optimization model with shortest total distance and minimum time balance is established in the effective inspection area, and then a trajectory planning based on the Chaos Genetic Algorithm is put forward. Taking advantage of the Logistic chaos sequence, this algorithm makes sure the cross and variation points of Genetic Algorithm, ensuring the precision of algorithm convergence, impairing buffeting problem generated by large cross intensity. The algorithm is applied to the experimental simulation of aeronautical planning in this dissertation. Simulation results showed that this method improved the precision of genetic algorithm.