磷虾群算法优化模糊PID的海上加油储罐恒压控制方法
DOI:
CSTR:
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:


Optimization of Fuzzy PID Constant Pressure Control Method for Offshore Refueling Tanks Using Krill Swarm Algorithm
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    本文聚焦海上加油储罐恒压控制,深入分析储罐系统特性,确立以电动机变频调速实现恒压控制的物理机制,阐明调节定子电源频率可改变转子转速、控制油泵出油量以达成恒压。针对恒压控制需求,设计基于磷虾群算法优化的模糊PID控制器。选取定子电源频率为核心控制量,利用模糊推理动态调整PID增益,构建离散PID算法实时更新参数,解决传统模糊PID参数整定依赖经验、难达全局最优的问题。通过随机初始化种群、建立适应度函数、模拟群体智能协作与竞争,迭代逼近最优参数组合,提升系统鲁棒性、响应速度与稳态精度。在模糊控制过程中引入磷虾群算法对参数寻优,利用其独特拉格朗日模型平衡群体协作与随机探索,适应油流波动与负载扰动。同时,对输入值进行模糊化处理,设计模糊子集与量化函数,精细化反映海上复杂工况;制定模糊规则表,实现增益参数精准调节。采用加权平均法进行解模糊化处理,将模糊推理结果转化为实际控制信号,实现海上加油储罐恒压控制。实验结果表明,所提方法在恒压控制中,在5min可达到设定压力时间,F1值为0.96,波动范围小,表明该方法在动态响应、稳态精度及抗干扰能力方面表现优异,有效提高了海上加油储罐恒压控制效果。

    Abstract:

    This article focuses on constant pressure control of offshore refueling tanks, analyzes the characteristics of the tank system in depth, establishes the physical mechanism of constant pressure control through variable frequency speed regulation of electric motors, and explains that adjusting the stator power frequency can change the rotor speed and control the oil pump output to achieve constant pressure. Design a fuzzy PID controller optimized based on the krill swarm algorithm for constant pressure control requirements. Selecting the stator power frequency as the core control variable, using fuzzy reasoning to dynamically adjust the PID gain, and constructing a discrete PID algorithm to update parameters in real time, solving the problem of traditional fuzzy PID parameter tuning relying on experience and difficult to achieve global optimization. By randomly initializing the population, establishing fitness functions, simulating swarm intelligence collaboration and competition, iteratively approaching the optimal parameter combination, the system"s robustness, response speed, and steady-state accuracy are improved. Introducing the krill swarm algorithm in the fuzzy control process for parameter optimization, utilizing its unique Lagrangian model to balance group collaboration and random exploration, adapting to oil flow fluctuations and load disturbances. At the same time, the input values are fuzzified, and fuzzy subsets and quantization functions are designed to finely reflect the complex working conditions at sea; Develop a fuzzy rule table to achieve precise adjustment of gain parameters. Using the weighted average method for defuzzification processing, the fuzzy inference results are converted into actual control signals to achieve constant pressure control of offshore refueling tanks. The experimental results show that the proposed method can achieve the set pressure time in 5 minutes in constant pressure control, with an F1 value of 0.96 and a small fluctuation range. This indicates that the method performs well in dynamic response, steady-state accuracy, and anti-interference ability, effectively improving the constant pressure control effect of offshore refueling tanks.

    参考文献
    相似文献
    引证文献
引用本文
相关视频

分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2025-05-08
  • 最后修改日期:2025-06-19
  • 录用日期:2025-06-20
  • 在线发布日期:
  • 出版日期:
文章二维码