Energy- and Cost-Efficient Transmission Strategy in Networked UAV Control System with ADP Trajectory Tracking Control

In this paper, we consider a networked control system (NCS) with bidirectional network-induced delay, in which the control center needs to control the remote unmanned aerial vehicle (UAV) to complete the trajectory tracking task. The sensor of the remote controlled UAV adopts the event-triggered mechanism, and the control center uses the adaptive dynamic programming (ADP) method to generate control actions. The application of ADP method to NCS brings new transmission options, that is, transmitting control action or neural network (NN) model. There exists a fundamental tradeoff between different transmission options with different transmission energy consumption and tracking cost, which still receives little attention in the NCS design. To fill this gap, we propose a cost-based transmission strategy that can balance the average energy consumption and the average tracking cost. By deliberately making decisions on whether to transmit the control action or the NN model, the weighted sum of the average energy consumption and the tracking cost is minimized. Simulation results show that compared with the benchmark strategies, the proposed strategy can achieve a better compromise in the long-term average energy consumption and long-term average tracking cost, and can obtain better performance in a specific weight range.