Contents
Acknowledgements ……………………………………………………………………………………………. i
Abstract …………………………………………………………………………………………………………… ii
Keywords ……………………………………………………………………………………………………. iii
Contents …………………………………………………………………………………………………………. vi
List of Figures …………………………………………………………………………………………………. ix
List of Tables …………………………………………………………………………………………………. xii
Chapter 1 Introduction ……………………………………………………………………………………….. 1
1.1. Background ……………………………………………………………………………………….. 1
1.2. Literature Review ……………………………………………………………………………….. 2
1.3. Motivation and Objectives ……………………………………………………………………. 7
1.4. Dissertation Overview ………………………………………………………………………….. 8
Chapter 2 Unmanned Helicopter Mathematical Model…………………………………………….. 9
2.1. Equations of Motion ………………………………………………………………………………… 9
2.2. Rotation Equation ………………………………………………………………………………….. 10
2.3. Main Rotor Dynamic and Tail Rotor Dynamic …………………………………………… 11
2.4. Overall Model ………………………………………………………………………………………. 13
2.5. Yaw Dynamic……………………………………………………………………………………….. 14
2.6. Interim Summary …………………………………………………………………………………… 16
Chapter 3 System Identification …………………………………………………………………………. 17
3.1. Helicopter Sub-models …………………………………………………………………………… 17
3.2. Subspace Estimation Method …………………………………………………………………… 18
3.3. PEM ……………………………………………………………………………………………………. 19
3.4. Online Modeling of the Attitude ………………………………………………………………. 19
3.5. Levenberg–Marquardt Method ………………………………………………………………… 21
3.6. System Identification Procedure ………………………………………………………………. 21
3.7. Identification Results ……………………………………………………………………………… 24
3.7.1. Identity Results using the PEM and Subspace Method …………………………… 24
3.7.2. Identity Results of Online Modeling Using RBFNN ……………………………… 25
3.7.3. Identity Results of Yaw Dynamic Using LM method ………………………………… 26
3.8. Interim Summary …………………………………………………………………………………… 27
Chapter 4 Development of Autonomous Flight Controllers …………………………………….. 27
4.1. Adaptive Tracking Control Based on Neural Approximation for the Yaw Motion
……………………………………………………………………………………………………………………… 28
4.1.1. The Adaptation Law ………………………………………………………………………… 28
4.1.2. Stability Analysis ……………………………………………………………………………. 30
4.1.3. Algorithm of the Design System ………………………………………………………… 31
4.1.4. Simulation Results and Discussions ……………………………………………………. 34
4.2. Online Adaptive Learning-Based and Model Predictive Control with Exponential
Data Weighting ………………………………………………………………………………………………… 37
4.2.1. Discrete-Time Model Predictive Control …………………………………………….. 38
4.2.2. Exponential Data Weighting Algorithm ………………………………………………. 39
4.2.3. Algorithm ………………………………………………………………………………………. 40
4.2.4. Procedure of Tuning Parameters and Analysis of Stability ……………………… 42
4.2.5. Adaptive Learning-Based Algorithm for Pitch and Roll Motion ……………… 43
4.2.6. Architecture of the Autonomous Flight Controller ………………………………… 45
4.3. Interim Summary …………………………………………………………………………………… 47
Chapter 5 Development of a Simulation Environment …………………………………………… 48
5.1. Raspberry Pi3 Model B Characteristic ………………………………………………………. 48
5.2. Settling the network on X-Plane ………………………………………………………………. 49
5.3. Hardware-In-The-Loop…………………………………………………………………………… 51
5.3. Simulation ……………………………………………………………………………………………. 53
5.3.1. Ideal Environment …………………………………………………………………………… 53
5.3.2. Disturbance Environment …………………………………………………………………. 56
5.4. Interim Summary …………………………………………………………………………………… 60
Chapter 6 Conclusions ……………………………………………………………………………………… 61
6.1. Summary of Contribution ……………………………………………………………………….. 61
6.2. Future Work …………………………………………………………………………………………. 62
Reference ………………………………………………………………………………………………………. 63
Biography ……………………………………………………………………………………………………… 68
Publications ……………………………………………………………………………………………………. 69
Conferences …………………………………………………………………………………………………… 69
