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<p>Regulation of mean arterial blood pressure (MABP) in a critical care scenario is essential due to the challenges caused by external interferences, uncertainty, and nonlinear variations in model parameters. This research paper proposes a robust, excellent, and oscillation-free controller to regulate a delay control system, such as mean arterial blood pressure (MABP), during various medical scenarios, including anesthesia, emergency cases, and post-surgery recovery. A new flow direction algorithm (FDA)-optimized, Takagi–Sugeno-Kang (TSK) with Oustaloup’s recursive approximation-based, a novel fractional-order type-2 fuzzy logic controller, is developed to administer sodium nitroprusside (SNP) properly, achieving the desired blood pressure levels under varying conditions. The recently developed FDA technique optimizes control parameters such as fractional-order parameters, scaling factors, and membership functions by minimizing the integral absolute error (IAE). Oustaloup’s recursive approximation is used for fractional-order approximation. The fractional-order approach provides greater flexibility and adaptability to complex systems. In addition, the proposed controller interval type-2 two-layer fractional-order fuzzy logic controller (IT2-TLFOFLC) performance is compared with existing interval type-2 two-layer integer-order FLC (IT2-TLIOFLC) and proportional-integral-derivative (PID) controllers. The simulation results demonstrate superior robustness and improved overshoot, settling time, and error reduction; recorded values of IAE for IT2-TLFOFLC, IT2-TLIOFL, and PID are 8056, 8327, and 9952&#xa0;mmHg, and corresponding settling times are 264.3, 277 and 304&#xa0;s, respectively. Additionally, the proposed controller is less sensitive to robustness challenges. Therefore, the results confirm that the proposed controller effectively handles delay complex systems while addressing external noise and parameter uncertainties, outperforming than conventional counterparts’ controllers.</p>

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A New Flow Direction Algorithm Optimized TSK Oustaloup’s Recursive Approximation-Based Novel Type-2 Fuzzy Logic Controller for Delay Control System

  • 期刊论文

  • 发表日期：

    2025年9月28日

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  • Ranjeet Prajapati,
  • Anupam Kumar,
  • Ardashir Mohammadzadeh

摘要

Regulation of mean arterial blood pressure (MABP) in a critical care scenario is essential due to the challenges caused by external interferences, uncertainty, and nonlinear variations in model parameters. This research paper proposes a robust, excellent, and oscillation-free controller to regulate a delay control system, such as mean arterial blood pressure (MABP), during various medical scenarios, including anesthesia, emergency cases, and post-surgery recovery. A new flow direction algorithm (FDA)-optimized, Takagi–Sugeno-Kang (TSK) with Oustaloup’s recursive approximation-based, a novel fractional-order type-2 fuzzy logic controller, is developed to administer sodium nitroprusside (SNP) properly, achieving the desired blood pressure levels under varying conditions. The recently developed FDA technique optimizes control parameters such as fractional-order parameters, scaling factors, and membership functions by minimizing the integral absolute error (IAE). Oustaloup’s recursive approximation is used for fractional-order approximation. The fractional-order approach provides greater flexibility and adaptability to complex systems. In addition, the proposed controller interval type-2 two-layer fractional-order fuzzy logic controller (IT2-TLFOFLC) performance is compared with existing interval type-2 two-layer integer-order FLC (IT2-TLIOFLC) and proportional-integral-derivative (PID) controllers. The simulation results demonstrate superior robustness and improved overshoot, settling time, and error reduction; recorded values of IAE for IT2-TLFOFLC, IT2-TLIOFL, and PID are 8056, 8327, and 9952 mmHg, and corresponding settling times are 264.3, 277 and 304 s, respectively. Additionally, the proposed controller is less sensitive to robustness challenges. Therefore, the results confirm that the proposed controller effectively handles delay complex systems while addressing external noise and parameter uncertainties, outperforming than conventional counterparts’ controllers.