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Cooperative State and Fault Estimation of Formation Flight of Satellites in Deep Space Subject to Unreliable Information

机译:信息不可靠的深空卫星编队飞行合作状态与故障估计

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In this paper, a novel distributed cooperative estimation framework for a formation flight of satellites is proposed. This framework is developed based on the notion ofsub-observers.Within a group of sub-observers each one is estimating certain states that are conditioned on a given input, output, and state information. In order to guarantee the ultimate boundedness of the estimation errors, a sub-observer dependency (SOD) digraph is introduced that is assumed to be acyclic. The overall estimation process is modeled by aweighted sub-observer dependency estimation (WSODE) digraph.By selecting an optimal path in the WSODE digraph, a high-level supervisor can then select and configure a set of sub-observers to successfully estimate all the system states. In presence of unreliable information due to large disturbances, noise, and actuator faults certain sub-observers may become invalid. In this case, the supervisor reconfigures the set of sub-observers by selecting a new path in the WSODE digraph such that the impacts of these uncertainties are managed and confined to only the local estimates of states and faults. This will consequently prevent the propagation of uncertainties to the entire estimation process and the performance degradations to the entire formation flight of satellites. Simulations are conducted for a five satellite formation flight system in deep space and the comparative results with a centralized Kalman filter (CKF) technique are shown to confirm the validity and advantages of our developed analytical work.
机译:本文提出了一种新型的编队卫星分布式协同估计框架。该框架是基于子观察者的概念开发的。在一组子观察者中,每个观察者都在估计以给定输入,输出和状态信息为条件的某些状态。为了保证估计误差的最终有界性,引入了假定为非循环的子观察者相关性(SOD)有向图。整个评估过程由加权子观察者依赖估计(WSODE)有向图建模,通过在WSODE有向图中选择最佳路径,高级主管可以选择并配置一组子观察者来成功估计所有系统状态。由于大的干扰,噪音和执行器故障而导致信息不可靠时,某些子观察者可能会失效。在这种情况下,监督者通过在WSODE有向图中选择一条新路径来重新配置子观察者集,以便管理这些不确定性的影响并将其仅限于状态和故障的本地估计。因此,这将防止不确定性传播到整个估计过程,并防止性能下降到整个卫星编队飞行。在深空中对五颗卫星编队飞行系统进行了仿真,并显示了使用集中式卡尔曼滤波器(CKF)技术的比较结果,以确认我们开发的分析工作的有效性和优势。

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