基于分层策略的多无人机最优协同航路规划

基于分层策略将多无人机协同航路规划分为航路规划层、协同控制层和航迹控制层进行研究。航路规划层采用基于K均值和遗传算法的航路规划方法,为每架无人机提供多条备选航路;针对传统协同控制算法在求解协同变量出现无解的情况,设计了新的协同变量求解步骤;航迹控制层基于无人机六自由度模型和协同变量建立了终端时间固定的最优航迹控制模型,并采用勒让德伪谱法将最优控制问题转化为非线性规划问题,并利用CFSQP对模型进行了求解,实现了对无人机航迹控制变量和姿态的规划。仿真结果表明,利用该方法得到的无人机协同航路具有较高的可操作性,且计算量较小,效率较高,得到的无人机控制指令平滑,易于操控。

An Optimal Coordination Trajectory Planning Method of Multiple Unmanned Air Vehicles Based on Hierarchy Strategy

A coordination trajectory planning method of multiple unmanned air vehicles (UAV) based on hierarchy strategy is researched, the research is divided in three hierarchies, i.e. route planning, coordination control and trajectory control. Multiple routes for each UAV are given based on K-means clustering algorithm and genetic algorithm. A new method is proposed to solve the problem that the use of the traditional algorithm could not find out the result of coordination variable. According to the six degree of freedom model and the coordination variable, a fixed terminal time optimal trajectory control model is built up for each UAV, thus the optimal control problem is converted to NLP problem with the LPM, and the model is solved by using CFSQP method, and then the plan of control parameters and attitude is realized. The simulation shows that the coordination trajectory of UAV obtained by this method is better in operability, less in computational complexity and higher in computational efficiency, and simultaneously the control command obtained is smooth and easy to operate.