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基于改进元启发式算法的蒸汽冷凝器压力调节非线性 FOPID 控制器设计。

Nonlinear FOPID controller design for pressure regulation of steam condenser via improved metaheuristic algorithm.

机构信息

Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.

Department of Computer Engineering, Batman University, Batman, Turkey.

出版信息

PLoS One. 2024 Sep 19;19(9):e0309211. doi: 10.1371/journal.pone.0309211. eCollection 2024.

DOI:10.1371/journal.pone.0309211
PMID:39298510
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11412520/
Abstract

Shell and tube heat exchangers are pivotal for efficient heat transfer in various industrial processes. Effective control of these structures is essential for optimizing energy usage and ensuring industrial system reliability. In this regard, this study focuses on adopting a fractional-order proportional-integral-derivative (FOPID) controller for efficient control of shell and tube heat exchanger. The novelty of this work lies in the utilization of an enhanced version of cooperation search algorithm (CSA) for FOPID controller tuning, offering a novel approach to optimization. The enhanced optimizer (en-CSA) integrates a control randomization operator, linear transfer function, and adaptive p-best mutation integrated with original CSA. Through rigorous testing on CEC2020 benchmark functions, en-CSA demonstrates robust performance, surpassing other optimization algorithms. Specifically, en-CSA achieves an average convergence rate improvement of 23% and an enhancement in solution accuracy by 17% compared to standard CSAs. Subsequently, en-CSA is applied to optimize the FOPID controller for steam condenser pressure regulation, a crucial aspect of heat exchanger operation. Nonlinear comparative analysis with contemporary optimization algorithms confirms en-CSA's superiority, achieving up to 11% faster settling time and up to 55% reduced overshooting. Additionally, en-CSA improves the steady-state error by 8% and enhances the overall stability margin by 12%.

摘要

管壳式换热器在各种工业过程中的高效传热中起着至关重要的作用。有效控制这些结构对于优化能源利用和确保工业系统可靠性至关重要。在这方面,本研究侧重于采用分数阶比例积分微分(FOPID)控制器来有效控制管壳式换热器。这项工作的新颖之处在于利用合作搜索算法(CSA)的增强版本来调整 FOPID 控制器,为优化提供了一种新方法。增强型优化器(en-CSA)集成了控制随机化算子、线性传递函数和自适应 p-最佳突变,与原始 CSA 相结合。通过对 CEC2020 基准函数的严格测试,en-CSA 表现出了强大的性能,优于其他优化算法。具体来说,与标准 CSA 相比,en-CSA 的平均收敛速度提高了 23%,解的准确性提高了 17%。随后,en-CSA 被应用于优化蒸汽冷凝器压力调节的 FOPID 控制器,这是换热器运行的一个关键方面。与当代优化算法的非线性比较分析证实了 en-CSA 的优越性,达到了高达 11%的更快的稳定时间和高达 55%的减少过冲。此外,en-CSA 将稳态误差提高了 8%,并将整体稳定裕度提高了 12%。

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