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Near real-time system identification in a wireless sensor network for adaptive feedback control

机译:无线传感器网络中的近实时系统识别,用于自适应反馈控制

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Migration of the identified system poles for a dynamical system indicates changes in its global properties. In civil engineering structures, these changes are most often due to changes in global stiffness or damping parameters associated with both environmental effects as well as deterioration of the structure. In structures that employ automated feedback control systems to mitigate unwanted vibrations, feedback control laws and state estimators (if used) are reliant upon a theoretical or identified model of the plant. Any loss in fidelity between the plant model and its actual condition will result in degradation of the controller performance. Low-cost, wireless control networks that by nature are more likely to utilize state-estimation, are therefore more vulnerable to problems associated with property changes in the system. In this paper, recursive identification of system poles is proposed for use in a wireless sensing network engaged in feedback control. Because it is based on system poles, the algorithm is ideally suited for adaptive control methods that update control and estimation gains as system properties change. The algorithm proposed is based on the fast transversal filter and is designed to minimize computation as well as data transmission requirements to optimally utilize the distributed data that is stored within a low-power wireless sensor network.
机译:动力系统中已识别系统极点的迁移表明其全局属性发生了变化。在土木工程结构中,这些变化通常是由于整体刚度或与环境影响以及结构退化相关的阻尼参数的变化。在采用自动反馈控制系统来减轻不必要的振动的结构中,反馈控制律和状态估计器(如果使用)依赖于工厂的理论模型或确定的模型。工厂模型与其实际条件之间的任何保真度损失都会导致控制器性能下降。本质上更可能利用状态估计的低成本无线控制网络因此更容易遭受与系统属性更改相关的问题。本文提出了系统极点的递归辨识方法,以用于参与反馈控制的无线传感网络。由于它基于系统极点,因此该算法非常适合于随系统属性变化而更新控制和估计增益的自适应控制方法。提出的算法基于快速横向滤波器,旨在最大程度地减少计算和数据传输需求,以最佳利用存储在低功率无线传感器网络中的分布式数据。

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