摘要
精准的航迹跟踪是无人机实现任务规划的必要条件。针对自适应优化制导律(AOGL)算法中,权重矩阵依靠先验知识或者试探选取、缺乏理论指导且未必最优的问题,提出了一种基于粒子群优化AOGL航迹跟踪方法。将权重矩阵中各元素经验值乘以待优化系数,代入黎卡提方程,推导出修正之后的制导律,进而构造目标函数进行寻优求解。在不同的扰动风速条件下,针对线性、圆形期望跟踪航迹分别进行数值仿真,结果表明,PSO-AOGL航迹跟踪效果更优,可有效降低跟踪位置误差。
Accurate path following is necessary for UAV mission planning.With respect to the problems of AOGL path following algorithm,which relies on prior knowledge or trial selection,lacks theoretical guidance and may not be optimal,a path following algorithm based on PSO-AOGL is proposed.By multiplying the empirical values of each element in the weight matrix with the coefficient to be optimized,the modified guidance law is derived by substituting the Riccati equation,and the objective function is constructed to find the optimal solution.Under different disturbance wind speed conditions,numerical simulations are carried out for linear and circular expected tracking paths respectively.The results show that PSO-AOGL has better tracking effect and can effectively reduce the tracking position error.
作者
门金柱
张本辉
王建国
姚科明
孙心丰
MEN Jinzhu;ZHANG Benhui;WANG Jianguo;YAO Keming;SUN Xinfeng(Dalian Naval Academy,Dalian 116000,China)
出处
《电光与控制》
CSCD
北大核心
2023年第7期91-94,共4页
Electronics Optics & Control
关键词
无人机
航迹跟踪
粒子群算法
自适应优化制导律
UAV
path following
particle swarm optimization
adaptive optimization guidance law
