摘要
基于一致性理论的多无人机分布式协同控制已广泛运用于无人机作战中,通过一致性控制算法实现状态一致完成协同需求。建立了集结问题的数学模型,基于协调变量和协调函数的分解策略进行求解。为实现协同控制的最优性,改进了平均一致性控制算法,采用Hamilton-Jacobi-Bellman方程给出基本优化一致性控制算法。在控制算法中引入过去状态差值,提高控制算法的动态响应性和能量最优性;同时采用遗传算法优化代价函数的加权矩阵,进一步提高控制算法的动态响应性和能量最优性,缩短了任务执行时间。理论分析和仿真实验验证了方法的有效性和可行性。
Distributed cooperative control of multi-UAV system based on consensus theory has been used widely in UAV operations,in which the consistent state and collaborative demand are achieved through consensus control algorithm .The mathematical description of gathering problem was established,the problem was solved under decomposition strategy based on the method of coordination variables and coordination function .To realize optimization of cooperative control,average consensus control algorithm was improved,the expression of basic optimized consensus control algorithm was given by Hamilton-Jacobi-Bellman equation.The method got better in terms of dynamic response and optimal cost by introducing outdated state difference to control algorithm .The weighted matrix of the cost function was optimized by genetic algorithm,the dynamic response and optimal cost was improved further .In the meanwhile,the task execution time was shortened .Theoretical analysis and simulation results verify the feasibility and effectiveness of the method .
出处
《电光与控制》
北大核心
2014年第8期24-32,共9页
Electronics Optics & Control
基金
国家自然科学基金(61273048)
关键词
多无人机系统
分布式协同控制
一致性理论
动态规划
multi-UAV system
distributed cooperative control
consensus theory
dynamic programming
