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Smith predictor controller design for TCP/AQM

Author

Listed:
  • Richa Sharma

    (Amity University Uttar Pradesh)

  • Purushottam Sharma

    (Amity University Uttar Pradesh)

  • Deepak Nagaria

    (Bundelkhand Institute of Engineering and Technology (BIET))

Abstract

Congestion is a major issue in any communication network. To alleviate this clog in the AQM (Active Queue Management) topology for TCP/IP networks is recommended. This structure’s goal is to reduce congestion by minimizing the size of the typical queue at the routers. Recently, several feedback strategies were developed to raise AQM. In this study, a fluid-flow model of TCP networks was used to create a Smith predictor controller designed for TCP/AQM. The advantage of using this controller is its capacity to predict a dynamic system’s state and thus reduce the effect of input delay inherent in TCP/IP flows. Smith predictor configuration is designed to attain reasonable process control with a long-dead time. The rising time, peak time, and settling time of the system are used to analyze its performance in the time domain. This designed controller contains two controllers proportional integral $${G}_{c1}$$ G c 1 and proportional derivative $${G}_{c2}$$ G c 2 for different purposes, specifically, the rejection of load disturbances and the time delay while simultaneously stabilizing the unstable process. The designing procedure for controllers $${G}_{c1}$$ G c 1 and $${G}_{c2}$$ G c 2 are self-determining. To provide robustness for process boundary uncertainties, a first-order filter is used. Simulation results demonstrate that the proposed technique’s performance is satisfactory and has improved robustness. It can be observed that the proposed framework can function in noisy environments.

Suggested Citation

  • Richa Sharma & Purushottam Sharma & Deepak Nagaria, 2023. "Smith predictor controller design for TCP/AQM," 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(6), pages 2460-2469, December.
    • Handle: RePEc:spr:ijsaem:v:14:y:2023:i:6:d:10.1007_s13198-023-02093-x
    DOI: 10.1007/s13198-023-02093-x
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    References listed on IDEAS

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    1. 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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