固定翼无人机编队的启发分布式模型预测控制

针对无人机编队飞行控制中队形保持、路径规划、重构、防撞等多重功能需求,采用启发型分布式模型预测控制框架,将需求转化为多目标优化问题中的代价函数与相容性约束求解,实现了对无人机编队飞行的一体化控制.同时,采用分阶段式的轨迹规划算法,融合模型预测轨迹规划与多项式轨迹规划,利用多项式轨迹系数实现高效的邻居轨迹信息交互,从而增大了模型预测控制的预测范围,并降低了规划控制过程中的计算量与通信量.最后,通过9架无人机的协同避障编队仿真,证明了该方法的有效性.

Fixed Wing UAVs Formation Control Based on Heuristic Distributed Model Predictive Control Method

In this paper, a heuristic Distributed Model Predictive Control(DMPC) method is proposed to deal with the problems of formation keeping, formation reconfiguration, collision avoidance and path planning of fixed wing UAVs simultaneously. The proposed method transforms all control requirements into cost functions and compatibility constraints, and solves control problems with the multi-objective optimization framework. A phased track planning method, which combines model predictive track planning and polynomial track planning methods, is proposed to increase the prediction horizon and reduce the computation complexity and communication load. A simulation example of formation control with nine UAVs is provided to demonstrate the practicability and effectiveness of this control method.