标题:Fault Estimation with Biased Process Noise Covariances
作者:Zhao, Ye; He, Xiao; Zhou, Donghua
通讯作者:Zhao, Y
作者机构:[Zhao, Ye; He, Xiao; Zhou, Donghua] Tsinghua Univ, Dept Automat, TNList, Beijing 100084, Peoples R China.; [Zhou, Donghua] Shandong Univ Sci & Techn 更多
会议名称:36th Chinese Control Conference (CCC)
会议日期:JUL 26-28, 2017
来源:PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017)
出版年:2017
页码:7190-7195
关键词:fault estimation; biased process noise; filter design; performance; analysis
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.
收录类别:CPCI-S
资源类型:会议论文
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