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- W4328007460 abstract "In this chapter, two novel methods are presented to handle two typical challenging problems in system identification, including asynchronous measurements and multiple outlier-corrupted measurements. These two methods are built based on the online dual-rate distributed identification framework elaborated in Chap. 6 . First, due to unavoidable imperfection of data acquisition systems, the measurements among different channels are generally asynchronous. Furthermore, since the sensing systems for civil engineering structures are usually exposed to severe service environment, the measurements are inevitable to be corrupted with outliers. Effective methods in an online manner are proposed to settle these challenging issues. Regarding the first issue of asynchronous data, since each sensor node uses only the data of its own in the proposed distributed identification method, the local model identification results are not affected by asynchronism of different sensor nodes. The proposed approach utilizes directly asynchronous data for online system identification. Regarding the second issue of outlier contamination, a hierarchical outlier detection approach is introduced. It detects the local outliers according to the outlier probability of the raw observations at the sensor nodes while it detects the global outliers according to the outlier probability of the local estimation results. The proposed methods can resolve the challenging problems of asynchronous measurements and multiple outlier-corrupted measurements effectively and achieve reliable identification results for time-varying dynamical systems in an online manner." @default.
- W4328007460 created "2023-03-22" @default.
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- W4328007460 date "2023-01-01" @default.
- W4328007460 modified "2023-09-30" @default.
- W4328007460 title "Online Distributed Identification Handling Asynchronous Data and Multiple Outlier-Corrupted Data" @default.
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- W4328007460 doi "https://doi.org/10.1007/978-981-99-0593-5_7" @default.
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