Unmanned aerial vehicles(UAVs) may play an important role in data collection and offloading in vast areas deploying wireless sensor networks, and the UAV’s action strategy has a vital influence on achieving applicabi...Unmanned aerial vehicles(UAVs) may play an important role in data collection and offloading in vast areas deploying wireless sensor networks, and the UAV’s action strategy has a vital influence on achieving applicability and computational complexity. Dynamic programming(DP) has a good application in the path planning of UAV, but there are problems in the applicability of special terrain environment and the complexity of the algorithm.Based on the analysis of DP, this paper proposes a hierarchical directional DP(DDP) algorithm based on direction determination and hierarchical model. We compare our methods with Q-learning and DP algorithm by experiments, and the results show that our method can improve the terrain applicability, meanwhile greatly reduce the computational complexity.展开更多
在相控阵天线跳波束对大范围潜在区域进行捷变覆盖的问题中,当前资源分配方法仅针对单一资源分配优化达到局部最优并未有统筹考虑,从空域、频域、时域、调制编码域等多个维度全面建立了相控阵跳波束下的资源联合分配优化模型,给出了一...在相控阵天线跳波束对大范围潜在区域进行捷变覆盖的问题中,当前资源分配方法仅针对单一资源分配优化达到局部最优并未有统筹考虑,从空域、频域、时域、调制编码域等多个维度全面建立了相控阵跳波束下的资源联合分配优化模型,给出了一种基于遗传算法和动态规划的模型求解方法。仿真结果表明,考虑了多维资源进行联合分配的方法,可有效降低卫星通信网络中各终端的缓存队列长度,从而提高用户服务质量(Quality of Service,QoS)及网络吞吐量。展开更多
基金supported by the National Natural Science Foundation of China(91648204 61601486)+1 种基金State Key Laboratory of High Performance Computing Project Fund(1502-02)Research Programs of National University of Defense Technology(ZDYYJCYJ140601)
文摘Unmanned aerial vehicles(UAVs) may play an important role in data collection and offloading in vast areas deploying wireless sensor networks, and the UAV’s action strategy has a vital influence on achieving applicability and computational complexity. Dynamic programming(DP) has a good application in the path planning of UAV, but there are problems in the applicability of special terrain environment and the complexity of the algorithm.Based on the analysis of DP, this paper proposes a hierarchical directional DP(DDP) algorithm based on direction determination and hierarchical model. We compare our methods with Q-learning and DP algorithm by experiments, and the results show that our method can improve the terrain applicability, meanwhile greatly reduce the computational complexity.
基金Supported by National Natural Science Foundation of China （61304079, 61125306, 61034002）, the Open Research Project from SKLMCCS （20120106）, the Fundamental Research Funds for the Central Universities （FRF-TP-13-018A）, and the China Postdoctoral Science. Foundation （201_3M_ 5305_27）_ _ _
文摘为有致动器浸透和未知动力学的分离时间的系统的一个班的一个新奇最佳的追踪控制方法在这份报纸被建议。计划基于反复的适应动态编程(自动数据处理) 算法。以便实现控制计划，一个 data-based 标识符首先为未知系统动力学被构造。由介绍 M 网络，稳定的控制的明确的公式被完成。以便消除致动器浸透的效果， nonquadratic 表演功能被介绍，然后一个反复的自动数据处理算法被建立与集中分析完成最佳的追踪控制解决方案。为实现最佳的控制方法，神经网络被用来建立 data-based 标识符，计算性能索引功能，近似最佳的控制政策并且分别地解决稳定的控制。模拟例子被提供验证介绍最佳的追踪的控制计划的有效性。
文摘在相控阵天线跳波束对大范围潜在区域进行捷变覆盖的问题中,当前资源分配方法仅针对单一资源分配优化达到局部最优并未有统筹考虑,从空域、频域、时域、调制编码域等多个维度全面建立了相控阵跳波束下的资源联合分配优化模型,给出了一种基于遗传算法和动态规划的模型求解方法。仿真结果表明,考虑了多维资源进行联合分配的方法,可有效降低卫星通信网络中各终端的缓存队列长度,从而提高用户服务质量(Quality of Service,QoS)及网络吞吐量。
