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研究生：	涂家瑋 Tu, Chia-Wei
論文名稱：	微機電慣性與定位整合之飛行控制 MEMS-Based INS/GPS Integration for Flight Control
指導教授：	林清一 Lin, Chin E.
學位類別：	碩士 Master
系所名稱：	工學院 - 航空太空工程學系 Department of Aeronautics & Astronautics
論文出版年：	2010
畢業學年度：	98
語文別：	英文
論文頁數：	123
中文關鍵詞：	無人飛行載具、飛行控制、慣性導航、微機電、卡漫濾波器
外文關鍵詞：	UAV, flight control, MEMS, INS, GPS, Kalman filter
相關次數：	點閱：79 下載：2
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本篇論文的主要目的是設計及驗證一個無人飛行載具(UAV)的飛行控制系統，包含機載設備及地面監控。機載設備是用來判斷及控制載具的自主飛行，並負責將無人飛行載具之飛行狀態通過即時傳輸至地面監控站。機載設備飛控系統是以 PID 控制理論為基礎的設計，具有橫向與縱向的控制模式，使載具能達到自主飛行的目的。載具的飛行狀態是由機載系統中的慣性導航 (INS) 與衛星定位 (GPS) 整合系統負責提供。本論文的慣性導航系統是以微機電 (MEMS) 感測器擷取飛行的動作變化，利用卡漫濾波器將衛星定位系統整合及演算得到即時的飛行狀態，此整合系統可以有效的提高導航系統的精確度及可靠度。在設計與製作完成後，本進行一些實驗以校正所設計之系統，並利用高度追蹤驗證飛控系統之能力。本論文完成飛行控制系統初步的驗證能用在研發中的無人飛行載具上。

An UAV flight control system is designed and implemented in this thesis. An airborne system for automatic command and control to autopilot the UAV is built to cooperate with a ground monitor station. The airborne system is mainly an INS/GPS integration system using several Micro Electro Mechanical System (MEMS) sensors to collect flight information and determine maneuver command to operate the UAV. The control modes for longitudinal and lateral performance are implemented using PID control concept. To improve system accuracy and eliminate environment interference, a Kalman filter is constructed into the airborne to improve the accurate and reliable of system performance. A series experiments are carried out to calibrate the system problems and accomplish flight operation missions in altitude tracking tests. A preliminary flight control system is verified for use in the developing UAV.

Abstract	i
摘  要	ii
致  謝	iii
CONTENTS	iv
LIST OF FIGURES	vii
LIST OF TABLES	x
CHAPTER I INTRODUCTION	1
1 Unmanned Aerial Vehicle (UAV)	1
2 Motivation	2
3 Objective	3
4 Thesis Outline	4
CHAPTER II FLIGHT CONTROL COORDINATES	5
1 Coordinate System	7
(a) Earth-Centered, Earth-Fixed (ECEF) Frame	7
(b) Earth-Centered Inertial (ECI) Frame	7
(c) Local Geodetic Frame	8
(d) Body Frame	9
2 Flight Dynamics	10
2.1 Euler Angles	10
2.2 Longitudinal Motion	11
2.3 Lateral Motion	12
3 GPS/INS Integration	14
3.1 Attitude Integral Equations	14
3.2 Direct Cosine Matrices (DCM)	15
3.3 ECEF to Geodetic Frame	16
3.4 Body-to-Navigation Frame	17
3.5 Quaternion	19
4 Velocity and Position Integral Equations	22
5 Earth Models	24
6 Kalman Filter	28
7 Coupled System	33
8 Kalman Filter Dynamic Matrixes	36
8.1 Velocity Error Model	37
8.2 Position Error Model	39
8.3 Attitude Error Model	40
9 Correction Equations	42
10 Remark	43
CHAPTER III CONTROL LAW DESIGN	45
1 Longitudinal Motion	45
1.1 Pitching Stabilization Controller	45
1.2 Velocity Controller	47
1.3 Height Controller	49
2 Lateral Motion	52
3 Integrated Automatic Control System	53
CHAPTER IV SYSTEM IMPLEMENT DESIGN	55
1 Common Implementations	55
1.1 Flight Vehicle	56
1.1.1 Arrow – 40	56
1.1.2 Cardinal – 71	57
1.2 Micro Control Unit - dsPIC33FJ128GP802	58
1.3 RF Transceiver Module	59
1.4 R/C Controller	59
1.5 Airborne PC	60
1.6 The Power System	61
2 GPS/INS Integrated System	61
2.1 Sensing Board	63
2.1.1 Accelerometer	64
2.1.2 Gyro scope	66
2.1.3 GPS module	67
2.2 KF Calculation Board	68
3 Automatic Control System Implement	69
3.1 Control Board	71
3.1.1 Control System	71
3.1.2 Sensing System	72
3.1.3 AC/RC Switching System	75
3.2 Mobile and Ground Station Systems	76
4 Electromagnetic Interference Design	78
5 Remark	80
CHAPTER V SYSTEM IDENTIFICATION	82
1 Pretests	82
1.1 Static Test	83
1.1.1 GPS/INS Integration System Components	83
1.1.2 Automatic Control System Components	85
1.2 Dynamic Test	88
1.3 Flight Test	89
2 Experiment of GPS/INS Integration System	94
2.1 Ground Test	94
2.2 Flight Test	101
3 Experiment of Automatic Control System	112
4 Remark	117
CHAPTER VI CONCLUSION	119
REFERENCES	121
VITA	123
                                    

[1] NOVA Science Programming on Air and Online, PBS Online, (2002), Available on web: http://www.pbs.org/wgbh/nova/spiesfly/uavs.html.
[2] U.S. Department of the Army, “Department of Defense Dictionary of Military and Associated Terms”, U.S. Department of Defense, (2009).
[3] T. H. Cox, C. J. Nagy, M. A. Skoog, I. A. Somers, “Civil UAV Capability Assessment”, National Aeronautics and Space Administration, (2004).
[4] UAV Market Space. Available on web: http://www.uavm.com/uavmarketspace.html.
[5] J. Farrell, M. Barth, “The Global Positioning System and Inertial Navigation”, McGraw-Hill, (1998).
[6] R. M. Rogers, “Applied Mathematics In Integrated Navigation Systems 3rd”, American Institute of Aeronautics and Astronautics, Inc., Reston, Virginia, (2007).
[7] Z. C. Hu, “The Utilization of a low cost Tightly Coupled INS/GPS Integrated System for Seamless Land Vehicle Navigation”, Master Thesis, Department of Geomatics, National Cheng Kung University, Tainan, Taiwan, (2009).
[8] H. T. Zhang, “Performance Comparison of Kinematic GPS Integrated with Different Tactical Grade IMUs”, Department of Geomatics Engineering, Master Thesis, University of Calgary, Calgary, Alberta, Canada, (2006).
[9] K. W. Lin, “The Development of A Low-cost MEMS Gyroscope/Global Positioning System Navigation System for UAV”, Master Thesis, Department of Aeronautics and Astronautics, National Cheng Kung University, Tainan, Taiwan, (2002).
[10] C. E. Lin, Y. H. Lai, Y. C. Huang, C. C. Li, C. J. Sun, C. W. Tu, C. C. Nien, C. C. Cheng, M. Y. Shih, “High Payload Low Speed UAV Design for Surveillance Applications”, Bristol UAV Conference, University of Bristol, UK, April 10-12, (2010).
[11] C. Huddleston, “Intelligent Sensor Design Using the Microchip dsPIC”, Newnes, London, United Kingdom (2006).
[12] Xsens Technologies B.V., Los Angeles, California. Available on web: http://www.xsens.com/.

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