Modeling of quadrotor UAV systems carrying a suspended payload and design of finite/fixed time adaptive sliding mode controller

In this thesis, it is aimed to model quadrotor UAV systems carrying suspended payloads and to design novel finite/fixed-time adaptive sliding mode controller for the modeled systems. First, a nonlinear model of a quadrotor carrying a suspended payload is obtained by considering parameter uncertainties and external disturbances. Then, a novel generalized model of an interconnected system consisting of more than one quadrotor carrying a suspended payload is developed. The system modelled in this study was developed to allow the payload to be carried by any number of UAVs. For this purpose, it is intended to obtain the nonlinear dynamic equations of the system by considering parameter uncertainties and external disturbances, and by evaluating the effects of the load on the quadrotors and the effects of the quadrotors on each other. In order to control the modelled systems, it is planned to design a novel finite/fixed time neural network based adaptive sliding mode controller. The controller structure to be designed will increase the effectiveness of the sliding mode control by learning the uncertainties in the system dynamics with the help of the neural network component and will significantly improve the amplitudes of the control signals. In addition, with the controller structure to be designed, it is aimed to determine the settling time, which is known as the time for the system states to reach the desired reference values, which is an important requirement in the control of nonlinear systems.