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研究生： 李佳勳
Li, Chia-Hsun
論文名稱： 簡易精準之多旋翼無人機飛控導航系統
Simplified Precision Navigation and Flight Control System for Multi-rotor UAV
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： 2016
畢業學年度： 104
語文別： 英文
論文頁數： 83
中文關鍵詞： 整合式導航系統 、自動駕駛系統 、卡爾曼濾波器 、自適應濾波 、多旋翼無人機
外文關鍵詞： Integrated Navigation System, Autopilot System, Kalman Filter, Adaptive Filter, Multi-Rotor UAV
相關次數： 點閱：120  下載：2 
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    • 近年來無人機的發展十分迅速，而比傳統直升機與定翼機有更多優勢與應用的多旋翼無人機，更是在這幾年發展成熟，從原本的學術與軍事用途擴展至商業、空拍與娛樂，為了飛航與人民的安全考量，各國開始制定無人機的相關法規，其中飛手需要執照的規定，可能會大大限制無人機的發展與應用，為了解決這個問題，無人機系統需要更精準的飛行與更容易的操作系統，而為了達到精準的飛控與導航，能準確估測無人機的動態是最大的關鍵，本研究使用低成本的感測器組成整合式導航系統，而有別於一般的資料融合演算法，本研究利用簡化的系統動態設計出低系統負擔的卡爾曼濾波器，並搭配利用感測器特性所設計出的自適應調變律，即時估算系統的狀態，使濾波器能在任何情況都能達到最佳狀態。
    透過精準的整合式導航系統，發展出任務型的自動導引與飛控系統，再透過本研究設計的全自動駕駛系統，讓沒有受過專業飛行訓練的人也能透過我們的系統完成所需的任務。

    Multi-rotor UAVs can be designed and fabricated for wide applications. Precision navigation and accurate flight control is the key to success. In design consideration, high precision sensors or low cost MEMS should be selected with technical and cost trade-off. Although MEMS sensors are useful, however, they might be devalued by significant errors due to noise and interference. To improve this defect, filters are generally introduced into system design to improve its performance. This paper presents a modified adaptive law for Kalman filter design to improve navigation accuracy by using low cost MEMS. An accurate estimation on covariance matrix Q and R in INS is divided into system covariance and measurement covariance from multiple sensor inputs. This tries to elevate filter function and reduce CPU load of the implemented microprocessor. System configuration is constructed with careful data processing. From off-line tests, the proposed modified adaptive Kalman filter has accomplished the required performance. A special design of bird expeller for agricultural or airfield applications is implemented and tested in a simple flight route. The system design realizes “one-touch” system concept to fly a small multi-rotor system with precision navigation in flight control. Formulation of the proposed adaptive low in Kalman filter design is presented into multiple sensors. In the flight control verification, take-off, cruise flight and landing are major parts to examine full automation to use the proposed multi-rotor system. The overall fabrication has been proven with excellent UAV design.

    摘要 I ABSTRACT II 致謝 III List of Figures VIII List of Tables XI Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Main Idea 2 1.3 Literature Survey 2 1.4 Scope 3 1.5 Thesis Outlines 4 Chapter 2 Theoretical review of Integrated Navigation System 5 2.1 Inertial Navigation System 5 2.1.1 Accelerometer 5 2.1.2 Gyroscope 6 2.1.3 Compass 7 2.1.4 Inertial Navigation System Algorithm 10 2.2 INS/GPS Integrated Navigation System 11 2.2.1 Loosely Coupled Integration 13 2.2.2 Tightly Coupled Integration 14 2.2.3 Strategies of Position Estimating 16 2.3 Integrated Altitude System 16 2.3.1 Barometer 17 2.3.2 Sonar 17 2.3.3 Strategies of altitude Estimating 19 2.4 Kalman Filter Algorithm 19 2.4.1 The Kalman Filter 20 2.4.2 Continuous-discrete Extended Kalman Filter 21 2.5 Adaptive Law of Kalman Filter 22 2.5.1 Fading Factor 22 2.5.2 Sage-Husa Adaptive Algorithm 24 2.6 Conclusion of Integrated Navigation System 25 Chapter 3 Design of Precision Navigation System 26 3.1 Filter Algorithm Design 26 3.1.1 Kalman Filter Design for Altitude 27 3.1.2 Kalman Filter Design for Positioning 28 3.2 Design of Acceleration State Estimator 29 3.3 Adaptive Law Design 31 3.3.1 Covariance of System Process 31 3.3.2 Covariance of Measurement Update 32 3.4 Concept of Adaptive Filter Design 33 Chapter 4 Adaptive Algorithm Implementation 35 4.1 Accelerometer Static Error Tracking 35 4.1.1 Bias Error 35 4.1.2 Gauss White Noise in Static 36 4.2 Accelerometer Dynamic Error Tracking 37 4.2.1 Scale Factor Error 38 4.2.2 Gauss White Noise in Dynamic 40 4.3 Gyroscope Error Tracking 41 4.3.1 Bias Error 41 4.3.2 Gauss White Noise 42 4.4 Discussion of Algorithm 43 Chapter 5 Avionics System Design 44 5.1 Communication System 45 5.1.1 Sensors Specification 46 5.1.2 Wireless Communication Module Specification 47 5.2 Navigation and Guidance System 47 5.2.1 Navigation System Design 48 5.2.2 Guidance System Design 49 5.3 Flight Control System 52 5.3.1 Roll and Pitch Controller Design 52 5.3.2 Yaw Controller Design 52 5.3.3 Altitude Controller Design 53 5.3.4 Navigation Controller Design 54 5.4 Ground Station System 55 5.5 Experiment Multi-rotor UAV 57 5.6 Conclusion of Avionics System 58 Chapter 6 Flight Verification of Autopilot System 60 6.1 Altitude Control Verification 60 6.1.1 Auto-Take-Off 61 6.1.2 Hover Control 62 6.1.3 Auto-Landing 63 6.2 Navigation Control Verification 64 6.2.1 Flight Verification of Integrated Navigation System 65 6.2.2 Flight Verification of Autopilot Guidance System 67 6.3 Low Battery Voltage Homing Flight 72 Chapter 7 Conclusion and Future Works 76 7.1 Conclusion of Autopilot System 76 7.2 Conclusion on the Proposed Algorithm 76 7.3 Future Works 77 References 79

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