基于贝叶斯优化算法的UCAV编队对地攻击协同任务分配  

Cooperative Task Allocation for UCAV Air-to-Ground Combat Based on Bayesian Optimization Algorithm

作　　者：张安[1] 史志富[1,2] 刘海燕[1,2] 何艳萍[1,2] 

机构地区：[1]西北工业大学,西安710072 [2]第二炮兵工程学院,西安710025

出　　处：《电光与控制》2009年第1期1-5,共5页Electronics Optics & Control

基　　金：陕西省自然科学基金资助项目(2006F45);高校博士点基金资助项目(20060699026)

摘　　要：针对UCAV编队对地攻击协同控制决策优化问题,首先构建了UCAV编队对地攻击任务分配的自主价值优势矩阵。在此基础上依据多人冲突理论分别对双方以及本机编队进行权重分配;建立了UCAV编队对地攻击协同任务分配的整体价值优势矩阵,由此根据决策变量与约束条件构建了任务分配问题的数学模型。然后应用贝叶斯优化算法对该模型进行了优化分析。仿真实例表明,所建协同任务分配模型能够反映编队协同控制决策的重要性,而且应用贝叶斯优化算法能够很快收敛到全局最优解,能有效地解决UCAV编队对地攻击的协同任务分配问题。In order to control and optimize cooperative air-to-ground combat decision-making of the Uninhabited Combat Air Vehicle （UCAV）, the self-determined advantage matrix of UCAV team is built firstly. Based on conflict theory, the weights of both sides and the aircraft formation are assigned respectively; the whole advantage matrix for task allocation of UCAV team is built based on the analysis. Accordingly, the mathematical model of task allocation is built based on the decision variables and constraints. The Bayesian Optimization Mgorithm （BOA） is utilized to optimize and analyze the model. The simulation results verified that the mathematical model of cooperative task allocation can reflect the importance of cooperative decisionmaking, the BOA can converge quickly to the global optimal solution and can effectively solve the cooperative task allocation problem of UCAV air-to-ground attack.

关 键 词：UCAV编队 对地攻击 任务分配 贝叶斯优化算法 

分 类 号：V271.4[航空宇航科学与技术—飞行器设计] TP391[自动化与计算机技术—计算机应用技术]