NDLI: Event-triggered fault estimation for nonlinear systems with missing measurements

Content Provider	IEEE Xplore Digital Library
Author	Yang Liu Zidong Wang Xiao He Donghua Zhou
Copyright Year	2014
Description	Author affiliation: Dept. of Autom., Tsinghua Univ., Beijing, China (Yang Liu; Zidong Wang; Xiao He; Donghua Zhou)
Abstract	In this paper, the joint fault and state estimation problem is investigated for a class of nonlinear systems with event-triggered transmissions and missing measurements. In the proposed event-triggered transmission scheme, in order to reduce unnecessary network traffic, the current measurement is released only when it changes greatly from the previously transmitted one. A Bernoulli distributed sequence taking values on 0 or 1 is introduced to govern possible missing measurements in the transmission. Special effort is made to obtain and then minimize certain upper bound of the estimation error covariance in the simultaneous presence of the linearization errors and imperfect measurement transmissions. It is noticeable that, in the proposed method, the traditional assumption on the availability on the probability density functions of the states and the innovations conditional on the measurements is no longer needed, and therefore the application scope is much widened. Moreover, the fault and states can be jointly estimated, thereby providing a way of simultaneously monitoring the system and diagnosing the faults. The estimator gain is calculated via solving two recursive matrix equations, and the corresponding algorithm is therefore suitable for online applications. An illustrative example is provided to show the effectiveness of the proposed algorithm.
Starting Page	5533
Ending Page	5538
File Size	145581
Page Count	6
File Format	PDF
ISBN	9789881563873
ISSN	19341768
DOI	10.1109/ChiCC.2014.6895885
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-28
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	TCCT, CAA
Subject Keyword	Estimation error nonlinear systems Upper bound missing measurements Current measurement Probability density function recursive algorithm Event-triggered transmission Nonlinear systems State estimation fault estimation
Content Type	Text
Resource Type	Article

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