Secure Tracking Control via Fixed-Time Convergent Reinforcement Learning for a UAV CPS

Abstract

Dear Editor, This letter is concerned with the secure tracking control problem in the unmanned aerial vehicle (UAV) system by fixed-time convergent reinforcement learning (RL). By virtue of the zero-sum game, the false data injection (FDI) attacker and secure controller are viewed as game players. Then, the attack-defense process is recast as a min-max problem. For solving the problem and acquiring the optimal secure control policy, a single-critic RL algorithm with fixed-time convergence is presented. Meanwhile, the associated convergence and stability proofs are given. A simulation is provided to show the effectiveness of the raised method.