多无人机任务集结合作博弈优化自组织协同控制

摘要

Multiple Unmanned Aerial Vehicle ( UAV) system self-organization cooperative operation based on consensus theory has become an effective operational mode for dealing with sudden tasks,mission rendezvous is the first action and vital part of self-organized cooperative control.After giving the problem description of self-organization cooperative and optimal control under the cooperative game framework,and establishing Pareto Solution Set of optimal control input,the basic cooperative game optimal consensus control algorithm is presented by Nash Bargaining Solution under self-organization cooperative control structure based on fast consensus control algorithm,which can achieve optimal control objectives such as optimal energy cost in the coordination process of system task status,dynamic response of cooperative control,timeliness of rendezvous action.After introducing outdated status difference into the basic algorithm, and optimizing the weighted matrix of the cost function by genetic algorithm,which is based on the fitness function constructed of optimal control targets,the improved cooperative game optimal consensus control algorithm is presented.Theoretical analysis and simulation results verify the feasibility and effectiveness of the method.%基于一致性理论的多无人机系统自组织协同作战是未来无人机应对突发任务的重要方式，任务集结是协同作战的首要行动和自组织协同控制的重要内容。为优化集结行动中系统任务状态协调过程能量最优性、协同控制动态响应性和集结行动时效性3个性能指标，采用基于快速一致性控制算法的协同控制结构，在合作博弈框架下给出多无人机系统自组织协同与优化控制问题描述，建立了优化控制输入的Pareto解集，采用Nash讨价还价方法给出基本合作博弈优化一致性控制算法。在基本算法中引入过去状态差值，并以优化目标构建适应度函数，采用遗传算法优化代价函数的加权矩阵，得到改进合作博弈优化一致性控制算法。理论分析和仿真实验验证了方法的可行性和有效性。