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Distributed moving horizon state estimation: Simultaneously handling communication delays and data losses

机译:分布式移动视野状态估计:同时处理通信延迟和数据丢失

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In this work, we consider distributed moving horizon state estimation of nonlinear systems subject to communication delays and data losses. In the proposed design, a local estimator is designed for each subsystem and the distributed estimators communicate to collaborate. To handle the delays and data losses simultaneously, a predictor is designed for each subsystem estimator. A two-step prediction-update strategy is used in the predictor design in order to get a reliable prediction of the system state. In the design of each subsystem estimator, an auxiliary nonlinear observer is also taken advantage of to calculate a reference subsystem state estimate. In the local estimator, the reference state estimate is used to generate a confidence region within which the local estimator optimizes its subsystem state estimate. Sufficient conditions under which the proposed design gives decreasing and ultimately bounded estimation error are provided. The effectiveness of the proposed approach is illustrated via the application to a chemical process example. (C) 2014 Elsevier B.V. All rights reserved.
机译:在这项工作中,我们考虑受通信延迟和数据丢失影响的非线性系统的分布式移动视界状态估计。在提出的设计中,为每个子系统设计了一个局部估计器,并且分布式估计器进行通信以进行协作。为了同时处理延迟和数据丢失,为每个子系统估计器设计了一个预测器。在预测器设计中使用了两步预测更新策略,以便获得对系统状态的可靠预测。在每个子系统估计器的设计中,还利用辅助非线性观测器来计算参考子系统状态估计。在局部估计器中,参考状态估计用于生成置信区域,局部估计器在该置信区域内优化其子系统状态估计。提供了足够的条件,在该条件下,所提出的设计给出了减小的误差并最终限制了估计误差。通过将其应用于化学过程示例,说明了所提出方法的有效性。 (C)2014 Elsevier B.V.保留所有权利。

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