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<Article>
<Journal>
				<PublisherName>University of Isfahan</PublisherName>
				<JournalTitle>Computational Intelligence in Electrical Engineering</JournalTitle>
				<Issn>2821-0689</Issn>
				<Volume>13</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2022</Year>
					<Month>03</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Low Frequency Stability Based on Optimal Design of Proportional-Integral-Deferential Fuzzy Controller-Fractional Order-Intelligent Hybrid Algorithm Based</ArticleTitle>
<VernacularTitle>Low Frequency Stability Based on Optimal Design of Proportional-Integral-Deferential Fuzzy Controller-Fractional Order-Intelligent Hybrid Algorithm Based</VernacularTitle>
			<FirstPage>103</FirstPage>
			<LastPage>120</LastPage>
			<ELocationID EIdType="pii">25380</ELocationID>
			
<ELocationID EIdType="doi">10.22108/isee.2020.122232.1353</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Mohammad</FirstName>
					<LastName>Eslami</LastName>
<Affiliation>Dept. of Electrical Engineering, Chabahar Branch, Islamic Azad University, Chabahar, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2020</Year>
					<Month>03</Month>
					<Day>22</Day>
				</PubDate>
			</History>
		<Abstract>In this paper, a new fractional-order fuzzy controller is proposed named proportional fuzzy+integral fuzzy+deferential fuzzy (FP + FIα + FDβ).The proposed controller in its structure is an integral, derivative gain with a fractional order.This controller is structurally adjustable with two fractional orders and is simply designed. This controller performs the stability process in a short time.The response time can also be changed by adjusting the coefficient of time scale α and β, which cause it to have a better performance compared to the classic PID controller. On the other hand, in the design of the proposed controller, the optimal adjustment of the controller gain and fuzzy members has turned into an optimization problem, which is done by a hybrid algorithm based on the VCS and the HBC colony (ABC) on the basis of a function in time realm.In the proposed hybrid algorithm, we had tried to take advantage of their local and final search powers to reduce the possibility of local presence dramatically.Investigations of different load variation scenarios, better performance of the proposed controller facing load disturbances from the root mean square, rise and fall time, will show the number of oscillations, and the fall time of the frequency changes.</Abstract>
			<OtherAbstract Language="FA">In this paper, a new fractional-order fuzzy controller is proposed named proportional fuzzy+integral fuzzy+deferential fuzzy (FP + FIα + FDβ).The proposed controller in its structure is an integral, derivative gain with a fractional order.This controller is structurally adjustable with two fractional orders and is simply designed. This controller performs the stability process in a short time.The response time can also be changed by adjusting the coefficient of time scale α and β, which cause it to have a better performance compared to the classic PID controller. On the other hand, in the design of the proposed controller, the optimal adjustment of the controller gain and fuzzy members has turned into an optimization problem, which is done by a hybrid algorithm based on the VCS and the HBC colony (ABC) on the basis of a function in time realm.In the proposed hybrid algorithm, we had tried to take advantage of their local and final search powers to reduce the possibility of local presence dramatically.Investigations of different load variation scenarios, better performance of the proposed controller facing load disturbances from the root mean square, rise and fall time, will show the number of oscillations, and the fall time of the frequency changes.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">intelligent hybrid algorithm</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Optimization</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">virus search colony</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">bee colony</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">fractional-order fuzzy controller</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Low Frequency Oscillations</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://isee.ui.ac.ir/article_25380_284d98b61f68f493a320d07a808aabff.pdf</ArchiveCopySource>
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