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Distributed state estimation in rotational shiftwork sensor networks with communication constraint

机译:具有通信约束的轮班传感器网络中的分布状态估计

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In this paper, a distributed state estimation problem is studied for a new class of rotational shiftwork sensor network with communication constraint. The main feature of such novel sensor networks is that only incomplete information is available for each sensor: (i) part of states of target plant can be detected; (ii) information exchanged among sensors suffered from randomly part loss. In this situation, the addressed distributed estimation problem would become more difficult, since less estimation information of the target system can be used. In practice, the batteries equipped for sensors are limited and non-replaceable. To reduce the power consumption, the sensors investigated here have two working modes: active and hibernated modes. In active mode, sensors can behave in a normal way, while in hibernated mode, a sensor has to cut off all the communication with environment to save energy. Two working modes alternate via a random variable. By resorting to Lyapunov functional method, a condition is derived for designing a distributed state estimator and ensure that the target plant can be estimated in mean square under certain criteria. In addition, a performance analysis of the shiftwork sensor networks is investigated.
机译:本文针对一类具有通信约束的新型轮班传感器网络,研究了分布状态估计问题。这种新颖的传感器网络的主要特征是每个传感器仅可获得不完整的信息:(i)可以检测到目标植物的部分状态; (ii)传感器之间交换的信息遭受随机的零件损失。在这种情况下,解决的分布式估计问题将变得更加困难,因为可以使用更少的目标系统估计信息。实际上,为传感器配备的电池是有限的且不可更换。为了降低功耗,此处研究的传感器具有两种工作模式:活动模式和休眠模式。在活动模式下,传感器可以以正常方式运行,而在休眠模式下,传感器必须切断与环境的所有通信以节省能源。两种工作模式通过随机变量交替出现。通过使用Lyapunov泛函方法,导出了设计分布式状态估计器的条件,并确保可以在某些条件下以均方值估计目标植物。此外,还研究了换档传感器网络的性能分析。

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