This thesis presents the trajectory tracking approach for a wall-climbing robot by using adaptive control schemes. The robot platform is configured with 2 active wheel motors, a suction motor, a motion controller, a battery set, and sensors. The platform's diameter is 25 cm, and its weight is 1.5 kg. The primary sensors are encoders and an accelerometer sensor, the sensors are used for measuring the robot's spatial orientation. The most important consideration for controlling the wall-climbing robot is to make sure that the wheels can be always well contacted to the wall regardless of the slope conditions without sacrificing robot’s mobility. To consider different slope conditions of the wall, this thesis proposes an adaptive gain sliding control schemes to alter the vacuum force so that different gravity effects can be properly dealt with. Moreover, the proposed vacuum force control approach can be desired to avoid the slips of wheels, as well as to reduce the power consumptions of wheel motors and suction motor. Practically, encoder and accelerometer sensors provide the spatial posture information for realizing adaptive control schemes. The sensors are connected to a field-programmable gate array (FPGA) based onboard motion controller to generate control inputs for wheel motors and suction motor according to a specific trajectory. Finally, MATLAB simulations and real tests for dealing with different surface slope conditions were performed with the trajectories of circle, triangle and rectangle. The results were evaluated according to the measurement of the accuracy of trajectory and the power consumptions of the wall climbing robots.

This thesis presents the trajectory tracking approach for a wall-climbing robot by using adaptive control schemes. The robot platform is configured with 2 active wheel motors, a suction motor, a motion controller, a battery set, and sensors. The platform's diameter is 25 cm, and its weight is 1.5 kg. The primary sensors are encoders and an accelerometer sensor, the sensors are used for measuring the robot's spatial orientation. The most important consideration for controlling the wall-climbing robot is to make sure that the wheels can be always well contacted to the wall regardless of the slope conditions without sacrificing robot’s mobility. To consider different slope conditions of the wall, this thesis proposes an adaptive gain sliding control schemes to alter the vacuum force so that different gravity effects can be properly dealt with. Moreover, the proposed vacuum force control approach can be desired to avoid the slips of wheels, as well as to reduce the power consumptions of wheel motors and suction motor. Practically, encoder and accelerometer sensors provide the spatial posture information for realizing adaptive control schemes. The sensors are connected to a field-programmable gate array (FPGA) based onboard motion controller to generate control inputs for wheel motors and suction motor according to a specific trajectory. Finally, MATLAB simulations and real tests for dealing with different surface slope conditions were performed with the trajectories of circle, triangle and rectangle. The results were evaluated according to the measurement of the accuracy of trajectory and the power consumptions of the wall climbing robots.

ABSTRACT i
ACKNOWLEDGEMENT ii
CONTENTS iii
LIST OF TABLES vi
LIST OF FIGURES vii
CHAPTER 1 1
1.1. Background of Research 1
1.2. Objectives of Research 3
1.3. Thesis Structure 3
CHAPTER 2 5
LITERATURE REVIEWs 5
2.1. Wall Climbing Robots 5
2.1.1. Legged Wall Climbing Robots 6
2.1.2. Wheeled Wall Climbing Robots 8
2.2. Adaptive Control 11
2.3. Accelerometer Introduction 13
CHAPTER 3 18
DESIGN AND IMPLEMENTATION 18
3.1. Mechanical Design 18
3.1.1. Vacuum Motor 18
3.1.2. Vacuum Chamber Seal 19
3.1.3. Locomotion Mechanism 20
3.2. Kinematic and Dynamic Modeling 21
3.2.1. Kinematic Modeling 21
3.2.2. Dynamic Modeling 23
3.3. Sliding Controller 28
3.4. FPGA Design 33
3.4.1. Software Design 34
3.4.2. Filter Module 40
3.4.3. ENC Module 41
3.4.4. PWM Module 42
3.4.5. ADC Module 43
3.4.6. Accelerometer Module 45
3.5. Odometry 46
3.6. Motion Capture 48
CHAPTER 4 49
SIMULATION RESULT AND DISCUSSION 49
4.1. Circle Trajectory Tracking Without Adaptive Gain Smooth Sliding Controller 49
4.4. Robust Adaptive Circle Trajectory Tracking 51
4.4. Robust Adaptive Triangle Trajectory Tracking 53
4.4. Robust Adaptive Rectangle Trajectory Tracking: 54
CHAPTER 5 56
EXPERIMENT RESULTS AND DISCUSSION 56
5.1. Odometry Calibration 56
5.2. Accelerometer Measurement 57
5.3. Measurement The Power Of The Suction Motor 58
5.4. Robust Adaptive Circle Trajectory Tracking 59
5.5. Robust Adaptive Triangle Trajectory Tracking 61
5.6. Robust Adaptive Rectangle Trajectory Tracking 62
5.7. Slope Changes 63
CHAPTER 6 65
CONCLUSION AND FUTURE WORKS 65
6.1. Conclusion 65
6.2. Future Works 66

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