无人机组网遥感实时任务观测的冗余容错控制方案

中小型无人机（UAV）越来越多地应用于各种实时静态和动态任务中,已成为对人类非常有用的辅助工具。适合无人机在各种条件下进行监视和测量的因素有很多,但无人机在执行不同的实时任务时仍会受到各种挑战,且一旦在任务执行过程中任何一个约束的及时响应缺失,将会影响任务的总体结果,导致整个任务部分或完全失败,在实际中很难建立完美系统。因此,在系统中引入冗余容错来最小化故障概率并增强其鲁棒性非常重要。其中,根本问题是随着系统复杂性的增加,除非对其采取补偿措施,否则其可靠性会急剧下降。冗余容错是通过添加一个或多个模块（通常采用并行配置）作为备份来引入冗余。为了提高极端条件下航空遥感任务无人机网络系统的鲁棒性和成功率,本文将基于冗余的容错控制技术引入无人机网络设计中,确定了不同限制条件下的最佳网络解决方案。组网设计是在不同观测条件下的遥感任务如“大尺度生态监测”、“中尺度洪灾监测”、“小尺度安全监测” 中,通过同步监控进行主动合作的包括多个无人机的网络。多无人机网络作为冗余容错体系结构时可以通过添加多个无人机作为备份使得系统可以容错,而无人机在不同极端条件下的位置和视角则可以作为冗余容错的场景设置。当组网方案中的无人机位置和视角超过设定的阈值时可以被认为是故障的,其将被分离并不考虑进一步分析。通过以上方式,无人机网络可以在极端条件下得到组网控制方案的有效输出,进而保证遥感观测任务的顺利进行。

Redundancy-Based Fault-Tolerance Control Schemes in UAV Networking for Real-Time Remote Sensing Monitoring Missions

Small to medium-sized unmanned aerial vehicles (UAVs) are increasingly been used in various real time static and dynamic missions, which make them very useful tool to assist men. There are several factors which make these UAVs suitable for monitoring and survey in a wide range of conditions. Despite of all these capabilities, certain factors remain the biggest challenge for extensive use of UAVs at individual level in different real-time missions. Moreover, once prompt response to any of these constraints during the mission execution is missed, can affect the mission’s overall results, leading to partial or complete failure of the whole mission. For such purpose introduction of redundant fault-tolerance into the system is very important in order to minimize the probability of failures and increase its robustness because it is practically impossible to build a perfect system. The fundamental problem is that, as the complexity of a system increases, its reliability drastically decreases unless compensatory measures are taken. The aim of redundant fault tolerance is to introduce redundancy by adding one or more modules as back-up usually in parallel configuration. To improve the robustness and success rate of UAV network systems for aerial remote sensing missions under extreme conditions, this paper introduced the redundancy-based fault-tolerance control technology into UAVs networking designs, and determined the best networking solutions with different restrictions. The devised networking design includes multi-UAV network with active cooperation through simultaneous monitoring during remote sensing missions such as "large-scale ecological monitoring," "medium-scale flood disaster monitoring," and "fine-scale security surveillance" under different observation conditions. The multi-UAV network serve as redundant fault-tolerant architecture where system could be fault tolerant through adding more than one UAVs as back-up. Scenarios set for the redundant fault-tolerance are UAVs position and viewing angle during different extreme conditions. The UAV(s) in network scheme is considered faulty when its position and viewing angle exceeds the set threshold and would be separated and not considered for further analysis. Only in this way, we can get effective output of the networking control solutions under extreme conditions to ensure that missions can be carried out smoothly.