基于MPC-PSO的无人机在线航迹规划  

UAV on-line Path Planning Based on Model Predictive Control and Particle Swarm Optimization in Complex Dynamic Environment

作　　者：李波[1] 屈原 徐向丽[1] LI Bo;QU Yuan;XU Xiang-li(Ordos Vocational College,Ordos 017000,China)

机构地区：[1]鄂尔多斯职业学院,内蒙古鄂尔多斯017000

出　　处：《内蒙古大学学报（自然科学版）》2018年第5期540-546,共7页Journal of Inner Mongolia University：Natural Science Edition

基　　金：内蒙古自治区高等学校科学研究项目(NJZC368)

摘　　要：研究了无人机在战场环境部分已知突然出现动态威胁情况下的三维在线航迹规划问题.采用"预规划-在线轨迹跟踪"的模式,根据已知的环境信息,离线规划出UAV的参考航迹.然后UAV在飞行过程中,需要在跟踪参考航迹的基础上,对UAV未来一段航迹进行预测,然后利用粒子群算法优化出UAV的最优(或次优)的飞行航迹.与传统的在线规划方法粒子群和稀疏A*搜索算法相比,该方法有效地提高了规划航迹的可行性和实时性,降低了算法的复杂度.仿真表明该算法是一种有效的无人机路径规划算法.The 3 Dreal time route planning of Unmanned Aerial Vehicles is studied when partial battle field information suddenly appears dynamic threats.The＂pre-planning and online trajectory tracking＂mode is used to first plan reference routes off-line for UAVs based on the known environment information.While UAVs are flying,the part of future routes is forecast based on tracking the reference routes.Then using the model of particle swarm algorithm the optimal（sub-optimal）route of UAV is obtained.Compared with traditional real-time route planning PSO and Sparse A＊Search,this method effectively improves the feasibility and instantaneity,and reduces the algorithm complexity.The simulation results show this algorithm is a effective route planning method of UAVs.

关 键 词：无人机 移动威胁 在线航迹规划 模型预测控制 粒子群算法 

分 类 号：V279[航空宇航科学与技术—飞行器设计]