<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="https://www.zbc.uz.zgora.pl/style/common/xsl/oai-style.xsl"?>
<OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" 
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/
         http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd">
	<responseDate>2026-04-03T19:34:53Z</responseDate>
	<request identifier="oai:zbc.uz.zgora.pl:94036" metadataPrefix="oai_dc" verb="GetRecord">
	https://zbc.uz.zgora.pl/oai-pmh-repository.xml</request>
	<GetRecord>
	
  <record>
	<header>
		<identifier>oai:zbc.uz.zgora.pl:94036</identifier>
	    <datestamp>2026-03-27T08:21:53Z</datestamp>
		  <setSpec>DigitalLibraryZielonaGora</setSpec> 	      <setSpec>DigitalLibraryZielonaGora:Repository:Faculties:FacultyComputerElectricalControl</setSpec> 	      <setSpec>DigitalLibraryZielonaGora:Repository</setSpec> 	      <setSpec>DigitalLibraryZielonaGora:Repository:Faculties</setSpec> 	      <setSpec>DigitalLibraryZielonaGora:Repository:TypesWork</setSpec> 	      <setSpec>DigitalLibraryZielonaGora:Repository:TypesWork:Articles</setSpec> 	    </header>
		<metadata>
	<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
<dc:title xml:lang="pl"><![CDATA[Predictive Optimal Iterative Learning Control for Nonlinear Systems using the Koopman Operator]]></dc:title>
<dc:creator><![CDATA[Tao, Xinyue]]></dc:creator>
<dc:creator><![CDATA[Tao, Hongfeng]]></dc:creator>
<dc:creator><![CDATA[Gao, Luyuan]]></dc:creator>
<dc:creator><![CDATA[Paszke, Wojciech (1975- )]]></dc:creator>
<dc:creator><![CDATA[Rogers, Eric]]></dc:creator>
<dc:subject xml:lang="pl"><![CDATA[iterative learning control]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[nonlinear systems]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[Koopman operator]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[predictive action]]></dc:subject>
<dc:description xml:lang="pl"><![CDATA[This paper develops a predictive optimal iterative learning control design for nonlinear systems based on the Koopman operator. Iterativa learning control applies to systems that make repeated executions, known as trials, over a finite duration, termed the trial length. Once a trial is complete, all information generated is available to update the control signal for the subsequent trial.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[The first step in design is to approximately model the nonlinear system as a high-dimensional linear model using the Koopman operator and extended dynamic mode decomposition, which is applied on each trial.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[Then, an iterative learning control law is designed with predictive action over an infinite duration in the trial-to-trial direction. The robust convergence of the tracking error is analyzed, and a numerical case study highlights the design`s effectiveness.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[artykuł zamieszczony w: "International Journal of Adaptive Control and Signal Processing"]]></dc:description>
<dc:date><![CDATA[2025]]></dc:date>
<dc:type xml:lang="pl"><![CDATA[artykuł]]></dc:type>
<dc:format xml:lang="pl"><![CDATA[application/pdf]]></dc:format>
<dc:identifier><![CDATA[http://www.zbc.uz.zgora.pl/Content/94036/SHENG_03_UZ.pdf]]></dc:identifier>
<dc:identifier><![CDATA[https://zbc.uz.zgora.pl/dlibra/publication/105868/edition/94036/content]]></dc:identifier>
<dc:identifier><![CDATA[oai:zbc.uz.zgora.pl:94036]]></dc:identifier>
<dc:language><![CDATA[eng]]></dc:language>
<dc:relation><![CDATA[oai:zbc.uz.zgora.pl:publication:105868]]></dc:relation>
<dc:rights xml:lang="pl"><![CDATA[Biblioteka Uniwersytetu Zielonogórskiego]]></dc:rights>
</oai_dc:dc>

</metadata>
	  </record>	</GetRecord>
</OAI-PMH>
