Thesis Type: Postgraduate
Institution Of The Thesis: Middle East Technical University, Graduate School of Natural and Applied Sciences, Turkey
Approval Date: 2020
Thesis Language: English
Student: MEHMET ANIL SEL
Supervisor: Ali Emre TurgutAbstract:
In this study, control and trajectory planning of a quadcopter system is presented for precise target engagement. Quadcopter system consists of a quadcopter body, a 2-DOF robotic arm mounted at the bottom and an object is held by the end-effector of the robotic arm. As for the dynamics of the quadcopter system is derived by using the kinematic relations of the system members. Equation of motion is obtained by using Lagrange-d’Alembert’s Principle. Then, object-target engagement is investigated by considering an adjustable trajectory. Two mission parameters which are the relative distance of the target and the release angle of the object are established for shaping the trajectory. The forward kinematics algorithm is developed for finding the engagement states. Reference inputs of the quadcopter system are optimized by minimization of the control effort. The trajectory of the quadcopter system is planned for the initial to engagement state of the quadcopter system. Firstly, the cascaded PID controller is designed by linearizing the equation of motion of the quadcopter system. The controller is tested with the existence of the motor and the sensor subsystems of the simulation environment. An object throwing scenario is executed by generating the control commands with trial error method. Cascaded PID controller is also implemented in the real physical system. Then, hardware dependent algorithms are developed in order to improve the flight performance. In addition to that, quadcopter’s moment of inertia is identified to have more realistic model of the system in the si mulation environment. Secondly, an infinite horizon LQR controller is developed for trajectory tracking. That controller is designed by considering the linearized equation of motion of the system. That controller structure is also tested in the same simulation environment. Precise target engagement is investigated while analyzing the energy consumption. All the proposed controller algorithms, kinematics and the dynamics of the quadcopter system are implemented in MATLAB/Simulink. Finally, the first controller structure is performed in the real physical system. However, both control algorithms are validated in simulation based experiments. In the framework, feasibility of the optimal trajectory with respect to both quadcopter system dynamics and the control inputs is guaranteed. Precise target engagement is achieved by the successive system performance.