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<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article">
	<front>
		<journal-meta>
			<journal-id journal-id-type="publisher-id">INFORMATICA</journal-id>
			<journal-title-group>
				<journal-title>Informatica</journal-title>
			</journal-title-group>
			<issn pub-type="epub">0868-4952</issn>
			<issn pub-type="ppub">0868-4952</issn>
			<publisher>
				<publisher-name>VU</publisher-name>
			</publisher>
		</journal-meta>
		<article-meta>
			<article-id pub-id-type="publisher-id">inf16406</article-id>
			<article-id pub-id-type="doi">10.15388/Informatica.2005.116</article-id>
			<article-categories>
				<subj-group subj-group-type="heading">
					<subject>Research article</subject>
				</subj-group>
			</article-categories>
			<title-group>
				<article-title>Learning Fuzzy Control of Nonlinear Processes</article-title>
			</title-group>
			<contrib-group>
				<contrib contrib-type="Author">
					<name>
						<surname>Kaminskas</surname>
						<given-names>Vytautas</given-names>
					</name>
					<xref ref-type="aff" rid="j_INFORMATICA_aff_000"/>
				</contrib>
				<contrib contrib-type="Author">
					<name>
						<surname>Liutkevičius</surname>
						<given-names>Raimundas</given-names>
					</name>
					<email xlink:href="mailto:r.liutkevicius@if.vdu.lt">r.liutkevicius@if.vdu.lt</email>
					<xref ref-type="aff" rid="j_INFORMATICA_aff_000"/>
				</contrib>
				<aff id="j_INFORMATICA_aff_000">Vytautas Magnus university, Vileikos 8, 44404 Kaunas, Lithuania</aff>
			</contrib-group>
			<pub-date pub-type="epub">
				<day>01</day>
				<month>01</month>
				<year>2005</year>
			</pub-date>
			<volume>16</volume>
			<issue>4</issue>
			<fpage>571</fpage>
			<lpage>586</lpage>
			<history>
				<date date-type="received">
					<day>01</day>
					<month>01</month>
					<year>2005</year>
				</date>
			</history>
			<abstract>
				<p>Due to high nonlinearities and time-varying dynamics of today's control systems fuzzy learning controllers find appliance in practice. The present paper proposes a method for the synthesis of the learning fuzzy controllers where an expert knowledge about a process is applied to form a learning mechanism that is used to acquire information for the knowledge base of the main fuzzy controller. According to the proposed method an expert knowledge is used to describe how the controller should learn to control rather than to control the process. The results of experiments on heating system and level/pressure system prove the practical relevance of the design strategy of a learning fuzzy controller.</p>
			</abstract>
			<kwd-group>
				<label>Keywords</label>
				<kwd>fuzzy control</kwd>
				<kwd>nonlinear control</kwd>
				<kwd>learning control</kwd>
				<kwd>level control</kwd>
				<kwd>pressure control</kwd>
				<kwd>temperature control</kwd>
			</kwd-group>
		</article-meta>
	</front>
</article>