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<p>In this study, the performance of a Continuous Stirred-Tank Reactor (CSTR) system is analysed. The performance of the Modified Proportional-Integral-Derivative (MPID) controller with a fractional filter can be improved by tuning independent control parameters. In this work, we propose a novel Modified Grey Wolf Optimizer (MGWO) technique to tune these parameters. These optimally tuned controller parameters enhance the performance of the CSTR system and achieve an optimal fitness function. To demonstrate the effectiveness of the proposed controller, it is compared with a Proportional-Integral (PI) controller, a Proportional-Integral-Derivative (PID) controller, and a PID controller with an integral filter (PIDF). All controllers are designed for the same CSTR system and tuned using different metaheuristic algorithms, with the Integral of Time Absolute Error (ITAE) as the single objective function and combination of ITAE and IAE as multi-objective function. The simulation results show the superiority of the proposed controller tunned with the novel MGWO by improving the performance of the CSTR system. The simulation results demonstrated that the proposed Modified PID controller tuned with Modified GWO outperforms the other designed controllers, showing a 31.76% reduction in ITAE compared to the PI controller, a 31.20% reduction compared to the PID controller, and a 30.99% reduction compared to the PIDF controller.</p>

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A novel modified grey wolf optimization tuned PID controller with fractional filter for the CSTR system

  • 期刊论文

  • 发表日期：

    2025年4月8日

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  • Ashish Sharma,
  • Manoj Kumar Kar,
  • Harsh Goud

摘要

In this study, the performance of a Continuous Stirred-Tank Reactor (CSTR) system is analysed. The performance of the Modified Proportional-Integral-Derivative (MPID) controller with a fractional filter can be improved by tuning independent control parameters. In this work, we propose a novel Modified Grey Wolf Optimizer (MGWO) technique to tune these parameters. These optimally tuned controller parameters enhance the performance of the CSTR system and achieve an optimal fitness function. To demonstrate the effectiveness of the proposed controller, it is compared with a Proportional-Integral (PI) controller, a Proportional-Integral-Derivative (PID) controller, and a PID controller with an integral filter (PIDF). All controllers are designed for the same CSTR system and tuned using different metaheuristic algorithms, with the Integral of Time Absolute Error (ITAE) as the single objective function and combination of ITAE and IAE as multi-objective function. The simulation results show the superiority of the proposed controller tunned with the novel MGWO by improving the performance of the CSTR system. The simulation results demonstrated that the proposed Modified PID controller tuned with Modified GWO outperforms the other designed controllers, showing a 31.76% reduction in ITAE compared to the PI controller, a 31.20% reduction compared to the PID controller, and a 30.99% reduction compared to the PIDF controller.