Finite‐Time Lyapunov‐Based Model Predictive Control of Unmanned Surface Vehicles Against Denial‐of‐Service Attacks: An Independent of Prediction Horizon Approach

ABSTRACT The resilience and robustness of model predictive control are typically contingent upon an adequately extended prediction horizon, yet it is constrained in real‐time applications by limited computational resources. To tackle this issue, this paper introduces a finite‐time Lyapunov‐based model predictive control (FTLMPC) approach, independent of the prediction horizon, for unmanned surface vehicles (USVs) subject to external disturbances and denial‐of‐service (DoS) attacks. Firstly, a finite‐time auxiliary control system is integrated within the FTLMPC framework. This system incorporates a finite‐time extended state observer (FTESO) for precise disturbance estimation and a finite‐time backstepping control law to guarantee zero tracking errors. Consequently, FTLMPC ensures finite‐time stability during each DoS attack interval, effectively preventing error accumulation despite the presence of disturbances and DoS attacks. Secondly, a novel compensation scheme is introduced to mitigate the information loss induced by DoS attacks, wherein the compensation signal is solely derived from the control signal at the moment of the last successful transmission, thus minimizing reliance on the prediction horizon. It enables flexible adaptation of the prediction horizon and control performance according to the available computational resources. Finally, the simulation results validate the superior control performance of the proposed strategy.