In order to enhance the capability of tracking targets autonomously of unmanned aerial vehicle (UAV), the partially observable Markov decision process (POMDP) model for UAV path planning is established based on the PO...In order to enhance the capability of tracking targets autonomously of unmanned aerial vehicle (UAV), the partially observable Markov decision process (POMDP) model for UAV path planning is established based on the POMDP framework. The elements of the POMDP model are analyzed and described. The state transfer law in the model can be described by the method of interactive multiple model (IMM) due to the diversity of the target motion law, which is used to switch the motion model to accommodate target maneuvers, and hence improving the tracking accuracy. The simulation results show that the model can achieve efficient planning for the UAV route, and effective tracking for the target. Furthermore, the path planned by this model is more reasonable and efficient than that by using the single state transition law.展开更多
In this paper we carried out a probabilistic analysis for a machine repair system with a general service-time distribution by means of generalized Markov renewal processes. Some formulas for the steady-state performan...In this paper we carried out a probabilistic analysis for a machine repair system with a general service-time distribution by means of generalized Markov renewal processes. Some formulas for the steady-state performance measures. such as the distribution of queue sizes, average queue length, degree of repairman utilization and so on. are then derived. Finally, the machine repair model and a multiple critcria decision-making method are applied to study machine assignment problem with a general service-time distribution to determine the optimum number of machines being serviced by one repairman.展开更多
文摘受到战争等特殊环境下部分节点导航拒止、节点移动性与环境干扰所带来的影响,快速进行测控网络拓扑重构是保证连续测控关键。为了解决上述问题,针对多体制无人集群测控网络的场景,提出一种基于多智能体深度确定性策略梯度(multi-agent deep deterministic policy gradient,MADDPG)的分布式多智能体测控网络群切换算法。该算法运用局部可观测马尔可夫决策模型,并考虑最小连通度、能耗与测控精度设计奖励函数,构建可靠的测控定位系统。仿真结果表明,该算法在不同的干扰环境下能有效抵抗外界干扰,保证测控定位的正常运行,与传统切换算法相比切换成功率提升12%以上。
基金supported by the Aeronautical Science Foundation of China(20135153031 20135553035 2017ZC53033)
文摘In order to enhance the capability of tracking targets autonomously of unmanned aerial vehicle (UAV), the partially observable Markov decision process (POMDP) model for UAV path planning is established based on the POMDP framework. The elements of the POMDP model are analyzed and described. The state transfer law in the model can be described by the method of interactive multiple model (IMM) due to the diversity of the target motion law, which is used to switch the motion model to accommodate target maneuvers, and hence improving the tracking accuracy. The simulation results show that the model can achieve efficient planning for the UAV route, and effective tracking for the target. Furthermore, the path planned by this model is more reasonable and efficient than that by using the single state transition law.
文摘In this paper we carried out a probabilistic analysis for a machine repair system with a general service-time distribution by means of generalized Markov renewal processes. Some formulas for the steady-state performance measures. such as the distribution of queue sizes, average queue length, degree of repairman utilization and so on. are then derived. Finally, the machine repair model and a multiple critcria decision-making method are applied to study machine assignment problem with a general service-time distribution to determine the optimum number of machines being serviced by one repairman.
