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Applying fuzzy logic and genetic algorithms to enhance the efficacy of the PID controller in buffer overflow elimination for better channel response timeliness over the Internet

机译:应用模糊逻辑和遗传算法来增强PID控制器在消除缓冲区溢出方面的功效,以提高Internet上的通道响应及时性

摘要

In this paper two novel intelligent buffer overflow controllers: the fuzzy logic controller (FLC) and the genetic algorithm controller (GAC) are proposed. In the FLC the extant algorithmic PID controller (PIDC) model, which combines the proportional (P), derivative (D) and integral (I) control elements, is augmented with fuzzy logic for higher control precision. The fuzzy logic divides the PIDC control domain into finer control regions. Every region is then defined either by a fuzzy rule or a 'don't care' state. The GAC combines the PIDC model with the genetic algorithm, which manipulates the parametric values of the PIDC as genes in a chromosome. The FLC and GAC operations are based on the objective function {0, Δ)2. The principle is that the controller should adaptively maintain the safety margin A around the chosen reference point (represent by the '0' of {0, Δ)2) at runtime. The preliminary experimental results for the FLC and GAC prototypes indicate that they are both more effective and precise than the PIDC. After repeated timing analyses with the Intel's VTune Performer Analyzer, it was confirmed that the FLC can better support real-time computing than the GAC because of its shorter execution time and faster convergence without any buffer overflow.
机译:本文提出了两种新型的智能缓冲区溢出控制器:模糊逻辑控制器(FLC)和遗传算法控制器(GAC)。在FLC中,现存的算法PID控制器(PIDC)模型结合了比例(P),微分(D)和积分(I)控制元素,并通过模糊逻辑进行了增强,以实现更高的控制精度。模糊逻辑将PIDC控制域划分为更精细的控制区域。然后通过模糊规则或“无关”状态定义每个区域。 GAC将PIDC模型与遗传算法相结合,遗传算法将PIDC的参数值作为染色体中的基因进行操纵。 FLC和GAC操作基于目标函数{0,Δ)2。原理是,控制器应在运行时自适应地将安全裕度A维持在所选参考点(由{0,Δ)2的“ 0”表示)附近。 FLC和GAC原型的初步实验结果表明,它们比PIDC更有效,更精确。在使用英特尔的VTune Performer Analyzer进行了重复的时序分析之后,可以确定的是FLC比GAC可以更好地支持实时计算,因为它的执行时间更短并且收敛速度更快,而且没有任何缓冲区溢出。

著录项

  • 作者

    Lin WWK; Wong AKY; Wu RSL;

  • 作者单位
  • 年度 2006
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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