Development of unmanned aerial vehicles with advanced safety capabilities - Zhang, Songyuan (2017)
Unmanned Aerial Vehicles (UAVs) have attracted a recurring interest in recent years. UAVs have been used to tackle critical tasks in a more efficient and safer way than ground robots in many situations. Since UAVs are often operating in complex environments such as forest, mountain, urban area, etc., in order to protect surrounding properties and people, a model based UAV control with advanced safety system is studied. A particular type of quadcopter is developed based on the characteristics of the platform and motors to increase flight stability and maneuverability. Kinematics and dynamics equations of the quadcopter are derived and system identification methods are applied to obtain the parameters of the model. Besides, a proportional-derivative (PD) controller is designed first. Further, to eliminate the steady state error and enhance the tracking performance, the controller is further improved to incorporate an integral control. To ensure that UAV stays inside the operating area and protect surroundings, an advanced safety system featured with dynamic soft geofence, fixed hard geofence, and real-time monitoring at the ground control station is developed. Dynamic soft geofence is used to predict the distance to the hard geofence boundary after a fixed time duration based on current location and the dynamics of the UAV. A model predictive control (MPC) approach is applied to design a controller for braking without breaching the hard geofence boundary. A simulator is created to simulate and visualize the quadcopter control mechanisms as well as path flying performance with the implemented geofence system. Simulations and experiments are carried out to verify the performance of the designed control and safety system.