Autonomous Reconfiguration Control Method for UAV’s Formation Based on Nash Bargain
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摘要: 针对任务环境下携带不同载荷的无人机(Unmanned aerial vehicles, UAVs)组成的编队, 为实现无人机间的相互支援和补充而进行编队重构控制, 运用多目标多人博弈理论, 将其转化为纳什谈判过程. 结合分布式模型预测控制(Distributed model predictive control, DMPC)方法, 设计一种基于纳什谈判的分布式预测控制(Nash bargaining solution-DMPC, NBS-DMPC)算法求解该问题, 并对算法收敛性进行了证明. 仿真实验表明, 该算法能够有效控制编队自主重构, 实现编队无人机间的威胁规避和协同保护, 同时能够有效降低无人机编队自主重构控制问题的求解规模.Abstract: For the formation consisting of unmanned aerial vehicles (UAVs) with different payloads in battlefield environment, in order to realize support and reinforce with each other, the control problem for formation reconfiguration of UAV is converted to the process of Nash bargain with a multi-player bargain problem. Combined with distributed model predictive control (DMPC), an new algorithm—NBS-DMPC (Nash bargaining solution-DMPC) is designed to solve this problem. The convergence of this algorithm is validated. Simulation results show that it can effectively control the self-reconfiguration of formation and achieve threat avoidance and cooperative protection. Also, this algorithm can effectively reduce the solution scale of the autonomous reconfiguration control problem.
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