Human-in-the-Loop Consensus Tracking Control for UAV Systems via an Improved Prescribed Performance Approach
Lei Chen, Hongjing Liang, Yingnan Pan, Tieshan Li
Abstract
In some crucial consensus tracking missions, the sign of the tracking error is not allowed to change during the tracking process. The existing tracking control schemes are unable to satisfy this requirement. To solve this issue, this work improves the conventional prescribed performance control (PPC) approach and applies it to the cooperative control of unmanned aircraft vehicle (UAV) systems. Moreover, the flight controller design incorporates human decision-making. This hybrid active interaction approach implies that humans and UAVs can execute complex and variable flight missions as a collaborative team. Considering that equipped motors are prone to faults when operating in harsh environments, this article presents an adaptive fuzzy fault compensation mechanism to ensure the flight safety of UAVs. Finally, the simulation study validates the effectiveness and control advantage of the proposed approach.