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    <journal-meta>
      <journal-id journal-id-type="nlm-ta">Rea Press</journal-id>
      <journal-id journal-id-type="publisher-id">null</journal-id>
      <journal-title>Rea Press</journal-title><issn pub-type="ppub">3042-1357</issn><issn pub-type="epub">3042-1357</issn><publisher>
      	<publisher-name>Rea Press</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">https://doi.org/10.48313/mtei.v1i3.59</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
        <subj-group><subject>Particle swarm optimization, Hydraulic Jack, Nonlinear dynamics, Proportional-integral-derivative controller, Position control</subject></subj-group>
      </article-categories>
      <title-group>
        <article-title>Particle Swarm Optimization-Based PID Control for Position Tracking of Nonlinear Hydraulic Servo Systems</article-title><subtitle>Particle Swarm Optimization-Based PID Control for Position Tracking of Nonlinear Hydraulic Servo Systems</subtitle></title-group>
      <contrib-group><contrib contrib-type="author">
	<name name-style="western">
	<surname>Jamali </surname>
		<given-names>Ali </given-names>
	</name>
	<aff> Department of Engineering, RMIT University, Melbourne, Australia.</aff>
	</contrib><contrib contrib-type="author">
	<name name-style="western">
	<surname>Malekee</surname>
		<given-names>Mojtaba </given-names>
	</name>
	<aff> Department of Mechanical Engineering, Faculty of Mechanical Engineering, University of Guilan, Rasht, Guilan, Iran.</aff>
	</contrib></contrib-group>		
      <pub-date pub-type="ppub">
        <month>09</month>
        <year>2024</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>19</day>
        <month>09</month>
        <year>2024</year>
      </pub-date>
      <volume>1</volume>
      <issue>3</issue>
      <permissions>
        <copyright-statement>© 2024 Rea Press</copyright-statement>
        <copyright-year>2024</copyright-year>
        <license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.5/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p></license>
      </permissions>
      <related-article related-article-type="companion" vol="2" page="e235" id="RA1" ext-link-type="pmc">
			<article-title>Particle Swarm Optimization-Based PID Control for Position Tracking of Nonlinear Hydraulic Servo Systems</article-title>
      </related-article>
	  <abstract abstract-type="toc">
		<p>
			Nonlinearity is inherent in hydraulic servomechanisms, as the flow rate-system pressure relationship is complex, and nonlinear friction and the fluid bulk modulus further complicate the system. This study aims to present an optimal Proportional-Integral-Derivative (PID) control method for the angular positioning of a hydraulic servo motor based on the Particle Swarm Optimization (PSO) technique. To improve the controller’s performance, an optimized multi-objective cost function is proposed that combines Integral Squared Error (ISE), maximum overshoot, and steady-state error criteria. An extensive nonlinear mathematical model of the hydraulic servo mechanism is designed and simulated in MATLAB/Simulink. Optimal PID parameter tuning using the PSO algorithm involves a swarm of 300 particles over 30 iterations. The simulation results show that the developed control scheme exhibits fast, accurate tracking of the reference signals without overshoot or oscillation. It takes approximately 4 seconds to track the shaft reference of the motor while maintaining tracking and system stability. This issue demonstrates the efficiency of the developed PSO-based PID controller for compensating nonlinearity without a nonlinear gradient technique. This technique offers a suitable control algorithm that requires fewer computing resources than other control techniques in the industrial application field, where the hydraulic servomechanism operates under nonlinear dynamics. 
		</p>
		</abstract>
    </article-meta>
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