An Integrated Control Architecture for a Cloud-based Unmanned Aerial Vehicle System with Lossy Networks

Unmanned Aerial Vehicles (UAVs) have been successfully employed in cooperative tasks over recent years, particularly in the applications for smart cities. In such scenario, a networked control system (NCS) framework is usually adopted since measurement and actuation data are mainly transmitted through communication networks. This paper proposes an integrated control architecture for a Cloud-based fixed-wing UAV system, where the control logic resides in the Cloud and sensing and actuating signals are transmitted over a realistic wireless network. The proposed control strategy leverages model predictive control (MPC) and a specialized Kalman filter in combination with two ad-hoc buffers, which enables simultaneous compensation for measurement and control input packet dropouts. Simulations of a nonlinear aircraft model show the effectiveness and advantages of proposed integrated scheme over an existing linear quadratic (LQ)-based control strategy.