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研究生: 曾偉
Tseng, Wei
論文名稱: 利用模糊邏輯控制於無人飛行載具自主導航編隊飛行模擬研究
Using Fuzzy Logic Control in Simulation of Autonomous Navigation and Formation Flight of Unmanned Aerial Vehicles
指導教授: 蕭飛賓
Hsiao, Fei-Bin
學位類別: 碩士
Master
系所名稱: 工學院 - 航空太空工程學系碩士在職專班
Department of Aeronautics & Astronautics (on the job class)
論文出版年: 2008
畢業學年度: 96
語文別: 英文
論文頁數: 76
中文關鍵詞: 編隊飛行無人飛行載具模糊邏輯控制
外文關鍵詞: unmanned aerial vehicles, fuzzy logic control, formation flight
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  • 在本論文中,我們利用模糊邏輯控制受控的飛行載具完成自主飛行,並且發展出一套導航點位移演算法使無人飛行載具完成設計的飛行隊形,其中受控無人載具需遵守依時序改變的導航點飛行,並由設限的飛行格式及油門調校控制來確保編隊飛行的完整性。即時飛行模擬平台被應用於實驗中,該硬體由兩部個人電腦組成,一端為控制端,另一端為模擬受控端,即時飛行模擬軟體則使用X-PLANE飛機飛行軟體,相關程式指令主要使用視窗環境開發的C及C++程式語言完成,所有演算法可經由即時模擬平台測試,並成功的由無人飛行載具的自主及多機同時飛行論證編隊飛行控制的可行性和強健性。

    In this thesis, the fuzzy logic control is used to accomplish the autonomous flight with a chosen vehicle by simulation, and develop the algorithm of shifting waypoints to constrain the UAVs always fly in a designed flight formation. The controlled UAVs flight follows the updating waypoints in sequence. Besides, the limited form and the throttle con-troller are employed to implement the formation flight completely. The architecture of the real-time simulation platform is applied in experiments, where the hardware is composed of two personal computers; one is used the commander and the other one is for simulation plant. While, the real-time simulation program uses the X-Plane aircraft flight software. The command program software primarily uses C and C++ languages with window develop environment. All the algorithms are tested by the real-time simulation platform that can successfully demonstrate the feasibility and robustness of the formation flight control for unmanned aerial vehicle’s autonomous flight and multiple-vehicle flight.

    中文摘要 III ABSTRACT IV ACKNOWLEDGEMENTS V CONTENTS VI LIST OF TABLES IX LIST OF FIGURES X LIST OF SYMBOLS XIV CHAPTER 1 INTRODUCTION 1 1.1 THE UAV AUTONOMOUS FLIGHT IN RMRL LAB OF NCKU 1 1.2 MOTIVATION AND OBJECTIVES 2 1.3 LITERATURE SURVEY 3 CHAPTER 2 NAVIGATION AND FORMATION FLIGHT CONTROL MODEL 9 2.1 THE DEFINITION OF THE COORDINATE FRAME 10 2.2 THE ATTITUDE CONTROL ARCHITECTURE 12 2.3 THE AUTONOMOUS NAVIGATION METHOD 13 2.4 THE FORMATION FLIGHT ALGORITHM 19 CHAPTER 3 FUZZY LOGIC CONTROL SYSTEM 25 3.1 FUNDAMENTAL CONCEPT OF FUZZY CONTROL THEORY 25 3.2 THE DESIGN METHOD OF FUZZY CONTROLLER 26 3.2.1 The Definition of Input and Output (I/O) Variables 26 3.2.2 The Decision of The Fuzzification Tactic 27 3.2.3 The Definition of linguistic Variable’s Data Base 28 3.2.4 The Design of Control Rule Base 33 3.2.5 The Design of Fuzzy Inference Engine 36 3.2.6 The Choice of Defuzzification Method 37 CHAPTER 4 THE SIMULATION ARCHITECTURE OVERVIEW 39 4.1 X-PLANE SOFTWARE SIMULATION ENVIRONMENT 39 4.2 THE REAL-TIME SIMULATION PLANT 42 4.2.1 The Data Transmission and Setting 42 4.2.2 The User Datagram Protocol Message Overview 45 4.2.3 Attitude Control in X-Plane Environment 46 4.2.4 The Real-Time Computation Flow Chart 47 4.3 GRAPHIC USER INTERFACE INTRODUCTION 49 CHAPTER 5 RESULTS AND DISCUSSION 52 5.1 THE SIMULATION OF AUTONOMOUS FLIGHT 52 5.2 THE SIMULATION OF FORMATION FLIGHT 56 5.2.1 Two UAVs Formation Flight 56 5.2.2 Three UAVs Formation Flight 65 CHAPTER 6 CONCLUSION 71 6.1 CONCLUDING REMARK 71 6.2 FUTURE PROSPECTIVE 72 REFERENCES 74 VITA 76

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