<p>This paper addresses the distributed containment control problem for autonomous surface vehicles (ASVs) with model uncertainties and external environmental disturbances under a structured cost index. A distributed fuzzy optimal control method based on a predictor-actor-critic architecture is proposed to achieve containment tracking control for ASVs. First, a finite-time data-driven fuzzy predictor is developed using integral concurrent learning to estimate the lumped uncertainties. Next, using the predictor and reference trajectories information, a performance index including tracking errors and control inputs is constructed. The corresponding Hamilton-Jacobi-Bellman (HJB) equation is derived to obtain the optimal control solution. Then, critic fuzzy logic systems (FLSs) are developed to approximate the unknown partial derivatives coupled with the control input in the HJB equation. Furthermore, actor FLSs are trained using a gradient descent method to approximate the critic FLSs. Finally, a distributed fuzzy optimal controller is designed based on the actor FLSs. Through Lyapunov stability analysis, it is proven that the closed-loop system is input-to-state practically stable. Simulation results demonstrate that the proposed distributed containment tracking control method is effective for ASVs based on the predictor-actor-critic architecture.</p>