Prescribed-Time Adaptive Fuzzy Tracking Control of UAV Swarms Under Deception Attack

Abstract

In addressing the tracking control problem for unmanned aerial vehicle (UAV) swarms, we consider several challenges: the unmeasurable state of the swarm system, potential deception attacks on actuators, external random disturbances, and the nonlinear dynamics of each UAV. To tackle these issues, we first introduce a time-varying function and utilize a coordinate transformation method to convert the time tracking problem into an error variable constraint problem. Next, we propose an adaptive time tracking control method employing one-to-one mapping and inversion techniques, aimed at achieving system convergence to a specified accuracy within a designated time frame. To mitigate the impact of possible deception attacks on actuators, we design an attack compensator that removes disturbances caused by time-varying attack gains. Additionally, we implement an observer to estimate the unmeasurable state of the system and utilize a fuzzy logic system to manage unknown functions. Finally, we validate the effectiveness of our control method through simulations.