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An approach to optimize performance of controller in networked control system

Author

Listed:
  • Richa Sharma

    (Amity University Uttar Pradesh)

  • Purushottam Sharma

    (Amity University Uttar Pradesh)

  • Anshuman Singh

    (Amity University Uttar Pradesh)

  • Veer Srivastava

    (Amity University Uttar Pradesh)

Abstract

The Network Control System, which includes three different nodes connected through a band-limited real-time digital network, was created as a result of industry evaluations modifying their specifications. An adequately stabilized controller is critical to maximizing the industry’s production rate. In this study, PID controller parameters Kp, Ki, and Kd (Gain coefficients of P (Proportional), I (Integral) and D (Derivative) controller) have been stabilized by using the Particle Swarm Optimization method followed by which performance indices have been calculated to observe the error rate on the calculated Kp, Ki, and Kd values. Compared with typical PID tuning approaches, particle swarm optimization tuning for controller parameters improves process properties such as time-domain requirement, supply interruptions, error reductions, and enhanced system reaction time. MATLAB/Simulink was used to run the simulations.

Suggested Citation

  • Richa Sharma & Purushottam Sharma & Anshuman Singh & Veer Srivastava, 2023. "An approach to optimize performance of controller in networked control system," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(5), pages 1639-1646, October.
    • Handle: RePEc:spr:ijsaem:v:14:y:2023:i:5:d:10.1007_s13198-023-01967-4
    DOI: 10.1007/s13198-023-01967-4
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    References listed on IDEAS

    as
    1. Ashraf F. Khalil & Jihong Wang, 2015. "Stability and Time Delay Tolerance Analysis Approach for Networked Control Systems," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-9, June.
    2. Purushottam Sharma & Kanak Saxena, 2017. "Application of fuzzy logic and genetic algorithm in heart disease risk level prediction," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 1109-1125, November.
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