Adaptive Communication and Control Co-Design for Remote UAV Systems

In this paper, we present a remote UAV control framework to achieve the tasks of trajectory tracking while avoiding collision. We utilize short-packet communication to transmit the control commands. Following this framework, we develop an improved self-triggered stochastic model predictive control (ST-SMPC) to adaptively adjust the control length, which greatly affects the control and communication performance. Moreover, chance constraints are considered to realize collision avoidance. Consequently, we decouple this co-design problem into a SMPC problem and a communication power optimization problem to jointly determine the control length. Simulation results demonstrate that the proposed control method can adaptively adjust the control length under various environments, achieving better communication efficiency compared to traditional MPC approaches.