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Franklin Inst.</a> <a href="/?q=in%3A501634" title="Articles in this Issue">360, No. 12, 9115-9138 (2023)</a>. </div> <div class="abstract">Summary: In this paper, active disturbance rejection control (ADRC) based on a neural network has been investigated for the attitude control of the hypersonic vehicle (HV) with uncertain disturbances, which are regarded as a strongly time-varying, nonlinear, and coupled system. The structure of nonlinear state error feedback (NLSEF) with an extended state observer (NLSEF+ESO) utilized in ADRC is considered to have good disturbance resistance ability in engineering applications with less dependence on the mathematical model of the system. However, the strong coupling of the HV makes it complicated to separately design ADRC for each channel. In addition, the bandwidth and parameters of the ESO can seriously affect the performance of the ADRC, while jitter occurs when they are not well matched. A cascade active-rejection control scheme is designed by introducing the radial basis function (RBF) neural network to substitute the ESO in ADRC, which mitigates the shortcoming of ADRC in addressing the control problems of the MIMO system with coupling disturbances. The NNESO can adapt well to disturbance characteristics through online training and fitting and can effectively reduce the jitter of the control. The stability of the NNESO is proved by Lyapunov stability theory, and the numerical simulations are presented to demonstrate the effectiveness of our theoretical results. In summary, the proposed NNESO-based cascade ADRC is an effective method for solving the problem of HV control with better disturbance resistance.</div> <div class="clear"></div> <br> <div class="citations"><div class="clear"><a href="/?q=rf%3A7732983">Cited in <strong>1</strong> Document</a></div></div> <div class="classification"> <h3>MSC:</h3> <table><tr> <td> <a class="mono" href="/classification/?q=cc%3A93B52" title="MSC2020">93B52</a> </td> <td class="space"> Feedback control </td> </tr><tr> <td> <a class="mono" href="/classification/?q=cc%3A93C10" title="MSC2020">93C10</a> </td> <td class="space"> Nonlinear systems in control theory </td> </tr><tr> <td> <a class="mono" href="/classification/?q=cc%3A93B53" title="MSC2020">93B53</a> </td> <td class="space"> Observers </td> </tr></table> </div><div class="keywords"> <h3>Keywords:</h3><a href="/?q=ut%3Aactive+disturbance+rejection+control">active disturbance rejection control</a>; <a href="/?q=ut%3Ahypersonic+vehicle">hypersonic vehicle</a>; <a href="/?q=ut%3Anonlinear+state+error+feedback">nonlinear state error feedback</a></div> <!-- Modal used to show zbmath metadata in different output formats--> <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">&times;</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;"> <!-- alert for connection errors etc --> </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"> <!-- Button trigger metadata modal --> <a type="button" class="btn btn-default btn-xs pdf" data-toggle="modal" data-target="#metadataModal" data-itemtype="Zbl" data-itemname="Zbl 1520.93162" data-ciurl="/ci/07732983" data-biburl="/bibtex/07732983.bib" data-amsurl="/amsrefs/07732983.bib" data-xmlurl="/xml/07732983.xml" > Cite </a> <a class="btn btn-default btn-xs pdf" data-container="body" type="button" href="/pdf/07732983.pdf" title="Zbl 1520.93162 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/10.1016/j.jfranklin.2022.09.019" aria-label="DOI for “Cascade ADRC with neural network-based ESO for hypersonic vehicle”" title="10.1016/j.jfranklin.2022.09.019">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">Sziroczak, D.; Smith, H., A review of design issues specific to hypersonic flight vehicles, Prog. 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