Smith Predictor-based Adaptive Control of Network-Controlled UAVs

Abstract

Assuming an imminent futuristic scenario, of 5G-and-Beyond communications networks, where different classes of autonomous unmanned aerial vehicles will use guidance, navigation and control systems relying on the network's performance, in this paper we investigate the delay and packet loss effects which may lead to closed-loop stability margins degradation of such aerial vehicles, causing accidents. The use of state observers can minimize these adverse effects by allowing these control systems to receive estimated data whenever sensor data is delayed or lost. In this sense, we propose the assessment of a Smith predictor-based selftuning control applied to a 6-DOF model of a network-controlled quadrotor. The investigation is focused on Proportional-Integral-Derivative control due to its solid acceptance as a trustworthy industrial technique. Simulations and robustness indices indicates that the investigated control approach can guarantee the robust stability of such aerial systems within the considered scenario.