标题:Fault estimation with biased process noise covariances
作者:Zhao, Ye ;He, Xiao ;Zhou, Donghua
作者机构:[Zhao, Ye ;He, Xiao ;Zhou, Donghua ] Department of Automation, TNList, Tsinghua University, Beijing; 100084, China;[Zhou, Donghua ] College of Electri 更多
会议名称:36th Chinese Control Conference, CCC 2017
会议日期:July 26, 2017 - July 28, 2017
来源:Chinese Control Conference, CCC
出版年:2017
页码:7190-7195
DOI:10.23919/ChiCC.2017.8028491
摘要:Fault estimation with performance analysis is investigated in the least squares sense for a class of time-varying systems with event-triggered measurement transmission and biased process noise covariances. In most other work, process noise covariance is assumed as either completely known. In this paper, we relax the assumption of knowing the exact process noise covariance and apply an event-triggered strategy when considering the measurement output transmission to remote estimator. A filter is designed in order to achieve the minimization on the upper bound of the filtering error covariance with event-triggered measurement transmission and biased process noise covariance. The desired filter parameters are calculated recursively with the least squares method, which is suitable for online application. It is found that the deviation of filtering error covariance is dependent on the deviation of process noise covariance with the performance of the proposed filter with biased process noise covariance further analyzed. A numerical simulation is utilized to illustrate the effectiveness of the proposed algorithm. © 2017 Technical Committee on Control Theory, CAA.
收录类别:EI
资源类型:会议论文
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