To address the challenge that unmanned surface vehicles (USVs) struggle to effectively balance tracking accuracy, control smoothness, and system energy efficiency under external disturbances, this paper proposes an anti-disturbance path tracking control method integrating quantum-inspired optimization (QIO) and dynamic game theory (GT). The proposed control method consists of a two-layer optimization architecture: the upper layer employs dynamic game theory to optimize the guidance process, modeling the optimization of the look-ahead distance ($Ld$) and switching radius ($R$) in the LOS guidance algorithm as a non-cooperative game, and achieves adaptive adjustment to path variations and environmental disturbances by solving for the Nash equilibrium. The lower layer, based on a quantum-inspired optimization algorithm, enhances the control process by employing quantum bit probability amplitude encoding for the PID parameter space and utilizing a quantum rotation gate mechanism for efficient global search, thereby achieving online self-tuning of PID parameters under environmental disturbances. Simulation results indicate that, under sea conditions with external disturbances, the proposed method achieves a superior balance among tracking accuracy, control smoothness, and system energy efficiency compared to the traditional fixed-parameter PID-LOS approach, enhancing the comprehensive anti-disturbance robustness of the USV.