In order to solve the engineering ships’ problem of difficult operation and low precision of cooperative control under complex sea states, this paper proposes a control strategy utilizing USVs to collaborate with an engineering mother ship for operational purposes. By using the nonlinear feedback method to improve the closed-loop gain-shaping algorithm, the tangent function is introduced to effectively solve the unstable problem of the control system for small USVs under complex sea states. Meanwhile, the motion of the mother ship is decoupled to establish the mathematical model of the headwind stationary state, and the improved closed-loop gain-shaping algorithm is applied to design the course-keeping controller and speed controller to effectively meet the dynamic positioning fixed-point control tasks of mother ships. The results show that the designed USV-engineering mother ship cooperative controller is effective under complex sea states. The control strategy is convenient and energy-saving, providing technical support for the improvement of informatization and the intelligence level of USV–mother ship cooperative control.

To improve the prediction reliability of model predictive control under model mismatch and environmental disturbances, this paper proposes a prediction-error-compensated MPC method with a forgetting factor for ship trajectory tracking and collision avoidance. The proposed method is developed within a Frenet-frame virtual ship group framework. A compensation term is introduced to correct the predicted heading-output sequence in the MPC prediction horizon, and a forgetting factor is used to regulate the influence of historical prediction errors on the current compensation term. Candidate trajectories are generated in the Frenet frame and evaluated using a hierarchical cost function to select a feasible obstacle avoidance path. Simulation experiments were conducted using the MMG model of the “Yukun” ship in three types of maritime encounter scenarios (head-on encounter, crossing encounter, and overtaking encounter) and a comprehensive obstacle scenario. The simulation results show that the proposed method can generate feasible local collision avoidance trajectories in complex obstacle environments and typical encounter scenarios, and maintain good trajectory tracking performance. It provides an effective scheme for trajectory tracking and collision avoidance of underactuated ships with great theoretical and practical value.