A novel applied cooperative control for drones will be proposed in this research. Compared to single drones, cooperative drones can complete their assigned tasks more efficiently due to their larger areas of coverage. Considering how rapidly actuators, computers and sensors are improving, the advancement of drone technology makes sense. Additionally, this can lead to the development of cooperative fixed-wing drones that have a much more advanced capability than a single unmanned aerial vehicle (UAV). To transport heavy loads, drones are expected to cooperate to meet the higher load capacity requirements. However, a single drone is often only able to lift a limited amount of weight and thus the study of multiple drone UAVs for cooperative transportation is urgent. Unlike a single drone system, the aerial transportation system with multiple drones has higher nonlinearities, degrees of freedom, and more complex couplings, which makes controlling these systems more challenging and complicated. This research focuses on the cooperative control of aerial transportation systems with multiple drones, proposing a control method to handle control problems of unknown system parameters, such as cable length, mass, and aerodynamic damping coefficients. As a result, the quadrotors are driven to their corresponding desired positions with accurate cargo swing suppression.
The aim of this study is to propose an applied cooperative control on drones and develop this approach to carry a slung payload. Carrying a payload is allocated to multiple drones, as a cooperative task for this purpose. This is a very challenging task because the payload will significantly alter the dynamics of the drones. Since payload states are difficult to measure and mass may change, a control strategy based on precise models may fail. Thus, we will examine the impact of change in mass of payload and the dynamics of drones for making a more realistic model. Finally, the performance of drones will be improved.
The project is supervised by Professor Jerome Jouffroy.
Contact information:
PhD student Fateme Aghaee - email: aghaee@sdu.dk, phone: +4565504832.