This paper proposes a null-space-based active disturbance rejection control （ADRC）allocation method to analyze the influence of multi-source disturbances encountered during the autonomous berthing of ships, such as environmental loads, bank effects, model uncertainties and control allocation errors.

First, a ship berthing motion model, multi-source disturbance model and control allocation model are established, and a neural network extended state observer (NNESO) is designed to estimate ship states and multi-source disturbances in real time. Second, null-space technology is introduced to design the control allocation algorithm. Based on this method, a scheme for stabilization control outside the berth and parallel berthing is realized. Finally, it is proven that all error signals of the autonomous berthing system under the proposed method remain uniformly ultimately bounded, ensuring the safety of the autonomous berthing process.

The comparative simulation results show that the proposed method has a trajectory tracking effect similar to that of the quadratic programming (QP) method, with a solution time of about 1.3% and a yaw maximum allocation error of 36.51% of the pseudo inverse (PI) method.

The proposed method not only ensures the accuracy of berthing motion control, but also significantly reduces the solution time and maximum allocation error, thereby ensuring real-time control allocation with high accuracy.