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系統識別號 U0002-2407201916184000
DOI 10.6846/TKU.2019.00795
論文名稱(中文) 輪型機器人主從式陣型模糊控制
論文名稱(英文) Formation Control of Mobile Robots with Leader-Follower Approach using Fuzzy Logic Controller
第三語言論文名稱
校院名稱 淡江大學
系所名稱(中文) 電機工程學系碩士班
系所名稱(英文) Department of Electrical and Computer Engineering
外國學位學校名稱
外國學位學院名稱
外國學位研究所名稱
學年度 107
學期 2
出版年 108
研究生(中文) 維非克
研究生(英文) Vivek Kumar
學號 604465012
學位類別 碩士
語言別 英文
第二語言別
口試日期 2019-05-30
論文頁數 33頁
口試委員 指導教授 - 劉寅春(pliu@mail.tku.edu.tw)
委員 - 江東昇(tschiang@uch.edu.tw)
委員 - 邱謙松(cschiu@dec.ee.cycu.edu.tw)
關鍵字(中) 非完整行動機器人
模糊控制器
方向誤差
距離誤差
模糊邏輯工具
編隊控制
關鍵字(英) Nonholonomic mobile robots
fuzzy logic controller
orientation error
distance error
fuzzy logic toolbox
formation control
第三語言關鍵字
學科別分類
中文摘要
本文介紹了基於模糊邏輯控制器設計通過實施領導者和跟隨者的方法,該方法允許建立和維護沿著給定軌跡移動之輪式移動機器人(WMR)的構造。 作為一組研究,控制器基於模糊邏輯控制器(FLC)設計,用於將移動機器人保持在所需的形式中。本論文考慮了領導者和跟隨者形成方法,模糊邏輯控制器將通過計算用於將移動機器人保持在列隊中的期望距離和期望角度來幫助維持移動機器人的構造。
英文摘要
This thesis presents the design of a fuzzy logic-based control by implementing the leader-follower approach that allows in establishing and maintaining the formations for the wheeled mobile robots (WMR) which moves along a predefined trajectory. As a set of research, th controller is designed based on the fuzzy logic controller (FLC) for keeping the mobile robots in the required formation. Leader-follower formation approach is considered for this thesis. Fuzzy logic controller will help in maintaining the formations of the mobile robots by calculating the desired distance and the desired angle for keeping the mobile robots in the formation.
第三語言摘要
論文目次
Contents	
Abstract in Chinese…………………………………………	  I
Abstract in English………………………………….……….	 II
Contents……………………………………………..….……	 III
List of Figures………………………………………………..	 V
1. Introduction………………………………………………..	 1
  1.1 Motivation………………………………….…..……….	 1
  1.2 Problem Statement…………………………………...…	 4
  1.3 Background………….…………………………………...	 5
  1.4 Literature Review…………………………………....…..	 6
2. Mobile Robot Modelling……………………………....…...	 9
  2.1 Kinematic Model…………………………………….…..	 9
  2.2 Leader-Follower Modelling…………………………..…	13
3. Control Strategies……………………………………….….	15
  3.1 Fuzzy Logic Controller………………………………......	15
3.1.1 Fuzzy Control………………………………….…..	15
3.1.2 Membership Function (MF)………………….…....	16
     3.1.2.1 Triangular Membership Function……...….	17
     3.1.2.2 Trapezoidal Membership Function…..........	18
3.1.3 Fuzzy Inference Systems………………………......	19
3.1.4	Defuzzification…………………………………….	19
4. Simulation Results…………………………………………..	21
5. Conclusion & Future Work…………………………………	28
6. References……………………………………………………	29











List of Figures	
	
1.1 Biological examples of multi agent systems in nature:
   (A)fireflies, (B)neuron firing, (C) flocking of migrating  
   birds and, (D)fish schooling……………………………….	 
 2
1.2 Examples of formation in practice applications:
   (a)Unmanned Air Vehicles (UAVs), (b) Autonomous 
   Underwater Vehicles, (c) Mobile Robots Systems (MRSs),    
   (d) Manipulation……………………………………………	 

 3
	
2.1 Unicycle Mobile Robot [25]………………………………	10
2.2	 Schematic of Leader-Follower Formation [22]…………...	13
	
3.1 Types of membership functions:	
(a)	triangular and (b) trapezoidal [31]……………………...	18
3.2 Process for the working of a fuzzy logic controller [31]…..	19
	
4.1 input-output of the FLC……………………………………	23
4.2 Membership function of the input variable(distance_error).	24
4.3 Membership function of the input variable (angle_error)…	24
4.4 Membership function of the output variable (v)…………..	25
4.5 Membership function of the output variable (w)…………..	25
4.6 Fuzzy Rule Base for the Controller………………………...	26
4.7 Graphical surface for the input-output variables…………...	26
4.8 Fuzzy Implication and Defuzzification Process…………...	27
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