基于MPC-PIO的无人飞行器集群编队重构控制

Formation reconfiguration control of UAV swarm based on MPC-PIO

针对存在各种障碍条件下的战场环境,为实现无人飞行器集群安全避障并进行快速精确打击,集群必须具备自主队形重构的能力。因此,建立了无人飞行器运动模型与领航跟随集群编队控制结构,并提出基于模型预测控制(MPC)框架的无人飞行器集群编队重构控制代价函数、避障代价函数及避碰代价函数,进一步运用鸽群优化(PIO)算法对重构问题进行优化求解。基于数值对比仿真实验结果,所提算法在集群编队跟踪误差和寻优速度方面表现出色。结果表明:所提算法能实现集群自主重构,并提高MPC方法的效率。

To realize security and accurate strikes under the battlefield environment with various obstacles,unmanned aerial vehicle swarm must possess the ability of self-formation reconfiguration.The unmanned aerial vehicle movement model and leader follower swarm formation control structure are established.The cost functions of unmanned aerial vehicle swarm formation control,obstacle avoidance and collision avoidance are proposed based upon the model predictive control(MPC)framework.The pigeon inspired optimization(PIO)algorithm is used to optimize the swarm formation reconfiguration control.Based on the results of numerical comparative simulations,the proposed algorithm has shown excellent performance in formation tracking error and optimization speed.The results indicate that the proposed algorithm is able to achieve autonomous formation reconstruction and significantly enhance the efficiency of the MPC method.