Outline

  • Abstract
  • Research Highlights
  • Keywords
  • 1. Introduction
  • 2. Fuzzy Logic Controller Applications
  • 3. Model Development in Fuzzy Logic
  • 3.1. Data Fuzzification
  • 3.2. Rule Format
  • 3.2.1. Membership Function
  • 3.2.2. Controller Surface Plot
  • 4. Overview of Simulation Environment
  • 4.1. Description of the Simulation Parameters
  • 4.2. Masc Model Development
  • 4.3. Controller Simulation Result
  • 5. Conclusion
  • Acknowledgment
  • References

رئوس مطالب

  • چکیده
  • 1. مقدمه
  • 2. کاربرد های کنترل کننده منطق نامعلوم
  • 3. توسعه مدل در منطق نامعلوم
  • 3.1 نامعلوم سازی داده
  • 3.2 فرمت غالب
  • 3.2.1 تابع عضویت
  • 3.2.2 طرح سطح کنترل کننده
  • 4. بازنگری محیط شبیه سازی
  • 4.1 توصیف پارامترهای شبیه سازی
  • 4.2 توسعه مدل MASC
  • 4.3 نتیجه شبیه سازی کنترل کننده
  • 5. نتیجه گیری

Abstract

This paper presents a fuzzy logic based controller (Multi-Agents System Controller (MASC)) which regulates the number of agents released to the network on a Multi-Agents Systems (MASs). A fuzzy logic (FL) model for the controller is as presented. The controller is a two-inputs-one-output system. The controllability is based on the network size (NTZ) and the available bandwidth (ABD) which are the inputs to the controller, the controller’s output is number of agents (ANG). The model was simulated using SIMULINK software. The simulation result is presented and it shows that ABD is the major constraint for the number of agents released to the network.

Research highlights ► Mobile agents should not be allocated indiscriminately on computer network ► Bandwidth and network size should be considered in allocating mobile agents ► Allocating too many agents to network leads to bandwidth wastage.

Keywords: - - - - -

Conclusions

A fuzzy logic based controller model is developed and simulated for a MASs. The controller promised to minimize bandwidth wastage due to excess agents routing communication network for given task. The developed system is very sensitive to available bandwidth, if the bandwidth is wide; likely the agent allocation to the network will be high subject also, to the number of computers or nodes on the network. The fuzzy logic capability to formalize approximate reasoning analysis is explored in this work to create a sensitive controller for MASs. If the model is implemented in real-life situation, it will reduce over flooding computer network with mobile agents in MASs.

دانلود ترجمه تخصصی این مقاله دانلود رایگان فایل pdf انگلیسی