Inspired by the limitations of traditional PID controllers and the different performance in ideal and realistic cases, the existing quadrotors, their applications and control methods have been intensively studied in this dissertation. Many challenges are shown: embedded quadrotor systems have limit computational resources and energy; the aerodynamic dynamics is rather complex and poorly known; environment has many disturbances and uncertainties; many control methods have been proposed in ideal scenarios in literature without comparison. Therefore, this dissertation focuses on these main points in control of quadrotors.A kinematic model and a dynamic model are proposed, including all the important aerodynamic forces and moments. A simplified dynamic model is also given based on some applications. Then, the dynamics of quadrotor is analyzed. Using the normal form theory, the model of quadrotor is simplified to a simplest form named the normal form, which exhibits all possible dynamic properties of the original system. The bifurcations of its normal form are then studied, and the system can be further simplified at its bifurcation point using the center manifold theory.Based on the research of the applications in the first chapter, five typical realistic scenarios are proposed: an ideal case, the cases with wind disturbance, parameter uncertainties, sensor noises and actuator faults. These realistic cases can show comprehensively the performance of control methods respect to the ideal cases. An event triggered scheme is also proposed with the time triggered scheme in order to further save computational resources. Then, a newly proposed method the model free control is presented. It is a simple but efficient technique for the nonlinear, unknown or partially known dynamics. A backstepping control and a sliding mode control are also proposed for the sake of comparison.All the control methods are implemented in the time and event triggered schemes in five different scenarios. In order to keep closer to realistic situations, the control gains of each methods are not changed in different scenarios. Based on the study in the first chapter, ten criteria are chosen for measuring the performance of control methods, such as the maximum absolute tracking error, the error variance, the actuation steps, the energy consumption, etc.
