Linear estimation for discrete-time periodic systems with unknown measurement input and missing measurements.
Sign Up to like & getrecommendations! Published in 2018 at "ISA transactions"
DOI: 10.1016/j.isatra.2018.11.013
Abstract: This paper considers the estimation problem for periodic systems with unknown measurement input and missing measurements. The missing measurements phenomenon is described by an independent and identically distributed Bernoulli process. The quality of the estimation… read more here.
Keywords: estimation; measurement input; unknown measurement; systems unknown ... See more keywords
Quantised polynomial filtering for nonlinear systems with missing measurements
Sign Up to like & getrecommendations! Published in 2018 at "International Journal of Control"
DOI: 10.1080/00207179.2017.1337933
Abstract: ABSTRACT This paper is concerned with the polynomial filtering problem for a class of nonlinear systems with quantisations and missing measurements. The nonlinear functions are approximated with polynomials of a chosen degree and the approximation… read more here.
Keywords: quantised polynomial; polynomial filtering; nonlinear systems; missing measurements ... See more keywords
Unbiasedness-constrained least squares state estimation for time-varying systems with missing measurements under round-robin protocol
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Systems Science"
DOI: 10.1080/00207721.2022.2031338
Abstract: In this paper, we present an unbiasedness-constrained approach to deal with the state estimation issue for a class of time-varying stochastic systems subject to missing measurements. The state estimates are generated from measurements collected by… read more here.
Keywords: state; missing measurements; state estimation; unbiasedness constrained ... See more keywords
Gaussian Filtering for Simultaneously Occurring Delayed and Missing Measurements
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DOI: 10.1109/access.2022.3208119
Abstract: Approximate filtering algorithms in nonlinear systems assume Gaussian prior and predictive density and remain popular due to ease of implementation as well as acceptable performance. However, these algorithms are restricted by two major assumptions: they… read more here.
Keywords: delayed missing; missing measurements; traditional gaussian; gaussian filtering ... See more keywords
An Event-Based Asynchronous Approach to Markov Jump Systems With Hidden Mode Detections and Missing Measurements
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Systems, Man, and Cybernetics: Systems"
DOI: 10.1109/tsmc.2018.2866906
Abstract: This paper is concerned with event-based $ {\mathcal {H}}_{ {\infty }}$ control for a class of networked Markov jump systems (MJSs) with missing measurements. The phenomenon of asynchronism occurs in both the controller and the… read more here.
Keywords: event based; jump systems; based asynchronous; missing measurements ... See more keywords
A Prediction-Based Approach to Distributed Filtering With Missing Measurements and Communication Delays Through Sensor Networks
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Systems, Man, and Cybernetics: Systems"
DOI: 10.1109/tsmc.2020.2966977
Abstract: This article addresses the prediction-based distributed filtering problem for a class of time-varying nonlinear stochastic systems with communication delays and missing measurements through the sensor networks. The phenomenon of the missing measurements is depicted by… read more here.
Keywords: distributed filtering; communication delays; prediction based; missing measurements ... See more keywords
Event-Triggered H ∞ Filtering for Markovian Jump Neural Networks under Random Missing Measurements and Deception Attacks
Sign Up to like & getrecommendations! Published in 2020 at "Complexity"
DOI: 10.1155/2020/4151542
Abstract: This paper concentrates on the event-triggered filter design for the discrete-time Markovian jump neural networks under random missing measurements and cyber attacks. Considering that the controlled system and the filtering can exchange information over a… read more here.
Keywords: neural networks; markovian jump; jump neural; missing measurements ... See more keywords