Document Zbl 1531.93417

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Control Appl. Methods</a> <a href="/?q=in%3A503457" title="Articles in this Issue">44, No. 1, 275-307 (2023)</a>. </div> <div class="abstract">Summary: This article is concerned with the centralized fusion (CF) robust steady-state Kalman filtering problem for a class of multisensor networked systems with mixed uncertainties including state-dependent and noise-dependent multiplicative noises, missing measurements, packet dropouts, and uncertain noise variances. By using a model transformation approach, the initial multisensor system under study is transformed into a multi-model multisensor system only with uncertain noise variances. By introducing an augmented state vector, the CF system is obtained. In the light of the minimax robust estimation method, and based on the worst-case fusion system with conservative upper bounds of uncertain noise variances, the CF robust steady-state Kalman estimators (predictor, filter, and smoother) are proposed in a unified form. By means of the permutation matrices and Lyapunov equation method, the robustness of CF estimators is proved. The accuracy relations among the robust local and fusion steady-state estimators are proved. An example applied to autoregressive moving average signal estimation is put forward, and the robust CF steady-state signal estimators are proposed. Simulation experiment shows the correctness of the proposed approach.<br class="zbmathjax-paragraph">{© 2022 John Wiley & Sons Ltd.}</div> <div class="clear"></div> <div class="classification"> <h3>MSC:</h3> <table><tr> <td> <a class="mono" href="/classification/?q=cc%3A93E11" title="MSC2020">93E11</a> </td> <td class="space"> Filtering in stochastic control theory </td> </tr><tr> <td> <a class="mono" href="/classification/?q=cc%3A93E10" title="MSC2020">93E10</a> </td> <td class="space"> Estimation and detection in stochastic control theory </td> </tr><tr> <td> <a class="mono" href="/classification/?q=cc%3A93B70" title="MSC2020">93B70</a> </td> <td class="space"> Networked control </td> </tr></table> </div><div class="keywords"> <h3>Keywords:</h3><a href="/?q=ut%3Acentralized+fusion">centralized fusion</a>; <a href="/?q=ut%3Aminimax+robust+estimation+method">minimax robust estimation method</a>; <a href="/?q=ut%3Amultisensor+networked+system">multisensor networked system</a>; <a href="/?q=ut%3Apacket+dropouts">packet dropouts</a>; <a href="/?q=ut%3Arobust+steady-state+estimators">robust steady-state estimators</a>; <a href="/?q=ut%3Auncertain+noise+variances">uncertain noise variances</a></div>  <div class="modal fade" id="metadataModal" tabindex="-1" role="dialog" aria-labelledby="myModalLabel"> <div class="modal-dialog" role="document"> <div class="modal-content"> <div class="modal-header"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> <h4 class="modal-title" id="myModalLabel">Cite</h4> </div> <div class="modal-body"> <div class="form-group"> <label for="select-output" class="control-label">Format</label> <select id="select-output" class="form-control" aria-label="Select Metadata format"></select> </div> <div class="form-group"> <label for="metadataText" class="control-label">Result</label> <textarea class="form-control" id="metadataText" rows="10" style="min-width: 100%;max-width: 100%"></textarea> </div> <div id="metadata-alert" class="alert alert-danger" role="alert" style="display: none;">  </div> </div> <div class="modal-footer"> <button type="button" class="btn btn-primary" onclick="copyMetadata()">Copy to clipboard</button> <button type="button" class="btn btn-default" data-dismiss="modal">Close</button> </div> </div> </div> </div> <div class="functions clearfix"> <div class="function">  <a type="button" class="btn btn-default btn-xs pdf" data-toggle="modal" data-target="#metadataModal" data-itemtype="Zbl" data-itemname="Zbl 1531.93417" data-ciurl="/ci/07754175" data-biburl="/bibtex/07754175.bib" data-amsurl="/amsrefs/07754175.bib" data-xmlurl="/xml/07754175.xml" > Cite </a> <a class="btn btn-default btn-xs pdf" data-container="body" type="button" href="/pdf/07754175.pdf" title="Zbl 1531.93417 as PDF">Review PDF</a> </div> <div class="fulltexts"> <span class="fulltext">Full Text:</span> <a class="btn btn-default btn-xs" type="button" href="https://doi.org/10.1002/oca.2950" aria-label="DOI for “Fusion steady-state robust filtering for uncertain multisensor networked systems with application to autoregressive moving average signal estimates”" title="10.1002/oca.2950">DOI</a> </div> <div class="sfx" style="float: right;"> </div> </div> <div class="references"> <h3>References:</h3> <table><tr> <td>[1]</td> <td class="space">Bar‐Shalom, Y.; Li, XR, Estimation and Tracking: Principle, Techniques and Software, 1993, Artech House, INC · <a href="/0853.62076" class="nowrap">Zbl 0853.62076</a></td> </tr><tr> <td>[2]</td> <td class="space">He, Y.; Wang, GH; Lu, DJ; Peng, YN, Multisensor Information Fusion with Applications, 2010, House Electron. 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