Complex multi-area collaborative coverage path planning in dynamic environments poses a significant challenge for multi-fixed-wing UAVs(multi-UAV).This study establishes a comprehensive framework that incorporates UAV...Complex multi-area collaborative coverage path planning in dynamic environments poses a significant challenge for multi-fixed-wing UAVs(multi-UAV).This study establishes a comprehensive framework that incorporates UAV capabilities,terrain,complex areas,and mission dynamics.A novel dynamic collaborative path planning algorithm is introduced,designed to ensure complete coverage of designated areas.This algorithm meticulously optimizes the operation,entry,and transition paths for each UAV,while also establishing evaluation metrics to refine coverage sequences for each area.Additionally,a three-dimensional path is computed utilizing an altitude descent method,effectively integrating twodimensional coverage paths with altitude constraints.The efficacy of the proposed approach is validated through digital simulations and mixed-reality semi-physical experiments across a variety of dynamic scenarios,including both single-area and multi-area coverage by multi-UAV.Results show that the coverage paths generated by this method significantly reduce both computation time and path length,providing a reliable solution for dynamic multi-UAV mission planning in semi-physical environments.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
Single gimbal control moment gyroscope(SGCMG)with high precision and fast response is an important attitude control system for high precision docking,rapid maneuvering navigation and guidance system in the aerospace f...Single gimbal control moment gyroscope(SGCMG)with high precision and fast response is an important attitude control system for high precision docking,rapid maneuvering navigation and guidance system in the aerospace field.In this paper,considering the influence of multi-source disturbance,a data-based feedback relearning(FR)algorithm is designed for the robust control of SGCMG gimbal servo system.Based on adaptive dynamic programming and least-square principle,the FR algorithm is used to obtain the servo control strategy by collecting the online operation data of SGCMG system.This is a model-free learning strategy in which no prior knowledge of the SGCMG model is required.Then,combining the reinforcement learning mechanism,the servo control strategy is interacted with system dynamic of SGCMG.The adaptive evaluation and improvement of servo control strategy against the multi-source disturbance are realized.Meanwhile,a data redistribution method based on experience replay is designed to reduce data correlation to improve algorithm stability and data utilization efficiency.Finally,by comparing with other methods on the simulation model of SGCMG,the effectiveness of the proposed servo control strategy is verified.展开更多
基金National Natural Science Foundation of China(Grant No.52472417)to provide fund for conducting experiments.
文摘Complex multi-area collaborative coverage path planning in dynamic environments poses a significant challenge for multi-fixed-wing UAVs(multi-UAV).This study establishes a comprehensive framework that incorporates UAV capabilities,terrain,complex areas,and mission dynamics.A novel dynamic collaborative path planning algorithm is introduced,designed to ensure complete coverage of designated areas.This algorithm meticulously optimizes the operation,entry,and transition paths for each UAV,while also establishing evaluation metrics to refine coverage sequences for each area.Additionally,a three-dimensional path is computed utilizing an altitude descent method,effectively integrating twodimensional coverage paths with altitude constraints.The efficacy of the proposed approach is validated through digital simulations and mixed-reality semi-physical experiments across a variety of dynamic scenarios,including both single-area and multi-area coverage by multi-UAV.Results show that the coverage paths generated by this method significantly reduce both computation time and path length,providing a reliable solution for dynamic multi-UAV mission planning in semi-physical environments.
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。
基金This work was supported by the National Natural Science Foundation of China(No.62022061)Tianjin Natural Science Foundation(No.20JCYBJC00880)Beijing Key Laboratory Open Fund of Long-Life Technology of Precise Rotation and Transmission Mechanisms.
文摘Single gimbal control moment gyroscope(SGCMG)with high precision and fast response is an important attitude control system for high precision docking,rapid maneuvering navigation and guidance system in the aerospace field.In this paper,considering the influence of multi-source disturbance,a data-based feedback relearning(FR)algorithm is designed for the robust control of SGCMG gimbal servo system.Based on adaptive dynamic programming and least-square principle,the FR algorithm is used to obtain the servo control strategy by collecting the online operation data of SGCMG system.This is a model-free learning strategy in which no prior knowledge of the SGCMG model is required.Then,combining the reinforcement learning mechanism,the servo control strategy is interacted with system dynamic of SGCMG.The adaptive evaluation and improvement of servo control strategy against the multi-source disturbance are realized.Meanwhile,a data redistribution method based on experience replay is designed to reduce data correlation to improve algorithm stability and data utilization efficiency.Finally,by comparing with other methods on the simulation model of SGCMG,the effectiveness of the proposed servo control strategy is verified.
