A quadcopter is a type of unmanned aerial vehicles (UAV). The industry of this type of UAVs is growing exponentially in terms of new technology development and the increase of potential applications that may cover construction inspections, search and rescue, surveillance, aerial photography, monitoring, mapping, etc. A quadcopter is a nonlinear and under-actuated system that introduces complex aerodynamics properties and create challenges which demands the development of new, reliable and effective control techniques to enhance the stability of flight control, plan and track a desired trajectory while minimizing the effect induced by the operational environment and its own sensors. Hence, many control techniques have been developed and researched. Some of such developments work well with the provision of having an accurate mathematical model of the system while other work is associated with a mathematical model that can accommodate certain level of wind disturbances and uncertainties related to measurement noise. Moreover, various linear, nonlinear and intelligent control techniques were developed and recognized in the literature. Each one of such control techniques has some aspect that excels in under certain conditions. The focus of this thesis is to develop different control techniques that can improve flight control stability, trajectory tracking of a quadcopter and evaluate their performance to select the best suitable control technique that can realize the stated technical flight control requirements. Accordingly, three main techniques have been developed: Standard PID, Fuzzy based control technique that tune PID parameters in real time (FPID) and a Hybrid control strategy that consists of three control techniques: (a) FPID with state coordinates transformation (b) State feedback (c) Sliding mode The configuration of the hybrid control strategy consists of two control loops. The inner control loop aims to control the quadcopter's attitude and altitude while the outer control loop aims to control the quadcopter's position. Two configurations were used to configure the developed control techniques of the control loops. These configurations are: (a) A sliding mode control is used for the outer loop while for the inner loop two control techniques are used to realize it: a Fuzzy gain scheduled PID with state coordinates transformation and a state feedback control. (b) Fuzzy gain scheduled PID control is used for the outer loop while for the inner loop two control techniques are used to realize it using the same formation as in (a) above. Furthermore, in order to ensure a feasible desired trajectory before tracking it, a trajectory planning algorithm has been developed and tested successfully. Subsequently, a simulation testing environment with friendly graphical User Interface (GUI) has been developed to simulate the quadcopter mathematical model and then to use it as a test bed to validate the developed control techniques with and without the effect of wind disturbance and measurement noise. The quadcopter with each control technique has been tested using the simulation environment under different operational conditions. The results in terms of tracking a desired trajectory shows the robustness of the first configuration of control techniques within the hybrid control strategy under the presence of wind disturbance and measurement noise compared to all the other techniques developed. Then, the second configuration of the control techniques came second in terms of results quality. The third and fourth results in the sequence shown by the fuzzy scheduled PID and the standard PID respectively. Finally, Validating the simulation results on a real system, a quadcopter has been successfully designed, implemented and tested. The developed control techniques were tested using the implemented quadcopter and the results were demonstrated and compared with the simulation results.
Robotics, Control & Smart Systems Program
MS in Robotics, Control and Smart Systems
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Committee Member 2
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(2018).Quadcopter: Design, modelling, control and trajectory tracking [Master’s thesis, the American University in Cairo]. AUC Knowledge Fountain.
Abouelsoud, Khaled. Quadcopter: Design, modelling, control and trajectory tracking. 2018. American University in Cairo, Master's thesis. AUC Knowledge Fountain.