摘要
任务调度包括任务分配和任务排序两个紧密耦合的问题,是多UCAV协同控制的核心和有效保证。分析了任务和UCAV的特性,针对带时间约束的复杂情况,建立了多机协同任务调度的数学模型。通过建立可行解到粒子间的映射,设计了粒子群优化算法求解,仿真实验验证了算法的可用性和有效性。
Task scheduling was an integration of task allocating and task ordering which coupled tightly. As one of the core steps to effectively exploit the capabilities of cooperative control of multiple unmanned combat aerial vehicles （UCAVs）, it was difficulty to be modeled. By analyzing the characters of tasks and UCAVs, a general mathematics model was proposed, which was a combined optimizing model. By defining a suitable particle structure, an algorithm based on the principles of particle swarm optimization was designed. Simulation results indicate that the algorithm is feasible and effective.
出处
《系统仿真学报》
EI
CAS
CSCD
北大核心
2007年第16期3623-3626,共4页
Journal of System Simulation
关键词
无人作战飞机
协同控制
任务调度
粒子群优化
UCAV
Cooperative Control
Task Scheduling
Particle Swarm Optimization
