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<dc:title xml:lang="pl"><![CDATA[Fuzzy and neural control of an induction motor]]></dc:title>
<dc:creator><![CDATA[Denai, Azzedine Mouloud]]></dc:creator>
<dc:creator><![CDATA[Attia, Sid Ahmed]]></dc:creator>
<dc:subject xml:lang="pl"><![CDATA[fuzzy control]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[neural networks]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[induction motor]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[vector control]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[speed observer]]></dc:subject>
<dc:description xml:lang="pl"><![CDATA[This paper presents some design approaches to hybrid control systems combining conventional control techniques with fuzzy logic and neural networks. Such a mixed implementation leads to a more effective control design with improved system performance and robustness.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[While conventional control allows different design objectives such as steady state and transient characteristics of the closed loop system to be specified, fuzzy logic and neural networks are integrated to overcome the problems with uncertainties in the plant parameters and structure encountered in the classical model-based design.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[Induction motors are characterised by complex, highly non-linear and time-varying dynamics and inaccessibility of some states and outputs for measurements, and hence can be considered as a challenging engineering problem.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[The advent of vector control techniques has partially solved induction motor control problems, because they are sensitive to drive parameter variations and performance may deteriorate if conventional controllers are used. Fuzzy logic and neural network-based controllers are considered as potential candidates for such an application.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[Three control approaches are developed and applied to adjust the speed of the drive system. The first control design combines the variable structure theory with the fuzzy logic concept. In the second approach neural networks are used in an internal model control structure.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[Finally, a fuzzy state feedback controller is developed based on the pole placement technique. A simulation study of these methods is presented. The effectiveness of these controllers is demonstrated for different operating conditions of the drive system.]]></dc:description>
<dc:publisher><![CDATA[Zielona Góra: Uniwersytet Zielonogórski]]></dc:publisher>
<dc:contributor><![CDATA[Korbicz, Józef (1951- ) - red.]]></dc:contributor>
<dc:contributor><![CDATA[Uciński, Dariusz - red.]]></dc:contributor>
<dc:date><![CDATA[2002]]></dc:date>
<dc:type xml:lang="pl"><![CDATA[artykuł]]></dc:type>
<dc:identifier><![CDATA[http://www.zbc.uz.zgora.pl/repozytorium/Content/58930/AMCS_2002_12_2_9.pdf]]></dc:identifier>
<dc:identifier><![CDATA[https://zbc.uz.zgora.pl/repozytorium/dlibra/publication/65725/edition/58930/content]]></dc:identifier>
<dc:identifier><![CDATA[oai:zbc.uz.zgora.pl:58930]]></dc:identifier>
<dc:source xml:lang="pl"><![CDATA[AMCS, volume 12, number 2 (2002)]]></dc:source>
<dc:source xml:lang="pl"><![CDATA[https://www.amcs.uz.zgora.pl/?action=paper&paper=87]]></dc:source>
<dc:language><![CDATA[eng]]></dc:language>
<dc:relation><![CDATA[oai:zbc.uz.zgora.pl:publication:65725]]></dc:relation>
<dc:rights xml:lang="pl"><![CDATA[Biblioteka Uniwersytetu Zielonogórskiego]]></dc:rights>
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