臺灣博碩士論文加值系統

本篇論文提出具有強健控制器之自我調變小腦模型控制器的差分-積分-微分控制器來控制自主垂直自轉的無人直升機以保證地面人員的安全。所提出的控制器透過改變主轉子來完成控制無人直升機的下降速度。由於差分-積分-微分控制器的參數很難去定義，因此加入小腦模型控制器來解決。然而，不同狀態下的動態會對應到不同差分-積分-微分控制器的參數。基於小腦模型控制器的差分-積分-微分控制器應用在調整差分-積分-微分參數以處裡不同情況下的動態。 此方法將使小腦模型的差分-積分-微分控制器擁有自我調整的能力。而所提出的方法將使任何直升機狀態下花上少許的時間來到所設定的目標速度。三個一維的小腦模型控制器以及強健控制器將運用在此研究上。此控制器的穩定度藉由李亞普諾夫方法來證明。模擬結果可證明所提出的控制器是有效的。

This thesis propose a self-tuning cerebellar model articulation controller based proportional-integral-derivative (CMAC-PID) controller with a robust controller to realize the autonomous vertical autorotation control for a unmanned helicopter to guarantee the security of ground staff. The proposed controller can control the sink rate of the unmanned helicopter by adjusting the main rotor’s pitch. However, the parameters of the PID controllers are difficult to be determined and the fixed parameters of the PID controller are not suitable for all conditions of the system’s dynamic. The PID controller based on the CMAC estimator is applied to solve the problem. This arrangement would lead the CMAC-PID controller has the ability of self-tuning. The present control technique can use less time for reaching the target speed in any helicopter states. Three one-dimension CMAC estimators and a robust controller are adopted in the thesis. By utilizing the Lyapunov theory, the stability of the proposed controller can be guaranteed. The simulation result is implemented to demonstrate the effectiveness of the proposed controller.

ACKNOWLEDGEMENTS i
ABSTRACT (IN ENGLISH) ii
ABSTRACT (IN CHINESE) iii
CONTENTS iv
LIST OF TABLES vi
LIST OF FIGURES vii
LIST OF SYMBOLS ix
CHAPTER
1 Introduction 1
2 Hardware 5
2.1 Unmanned Aerial Helicopter 6
2.2 ArduPilot-Mega 2.5 8
2.3 3DR radio 9
2.4 others 10
2.5 Mission Planner 11
3 PID and CMAC Neural Network 12
3.1 PID Controller 12
3.2 basic CMAC 13
3.3 One-Dimensional CMAC 14
4 Controller Design 19
4.1 Controller design 20
4.2 Stability Theorem 22
5 Simulation Result 26
5.1 Vertical Autorotation Model 26
5.2 Simulation result 30
6 Experiment 49
7 Conclusions 55
REFERENCES 56

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