Currently, accelerated research on automation is involved in most fields associated with vehicle manufacturing. In the area of autonomous operation of marine vehicles, automatic berthing remains a problem due to the nonlinearity of the low-speed maneuvering model, poor control of the vessel at low speed, and collision with berth danger. A previous study on off-line automatic berthing reveals frequent switching of the propeller revolution direction, which is impractical and must be prevented in case of a diesel engine. In this study, to overcome this problem, a new variable for the time to switch the propeller revolution direction is introduced and optimized. Also, we establish a more robust off-line control method for optimizing the required time and the final ship attitude by enhancing the objective function. Since the method provided here is still an off-line control method, its applicability to on-line control must consider the external force uncertainty and modeling error. The set of the optimal control input and trajectory obtained in this study, however, are applicable as an initial candidate for on-line predictive control modeling. Furthermore, the trajectory can serve as the desired path in a path-tracking problem.

当前，自动化的加速研究涉及与车辆制造相关的大多数领域。在海上车辆的自主操作领域中，由于低速操纵模型的非线性，低速下对船舶的不良控制以及与泊位危险的碰撞，自动泊位仍然是一个问题。脱机自动靠泊的先前研究表明，螺旋桨旋转方向的频繁切换是不切实际的，在柴油机中必须避免。在这项研究中，为克服此问题，引入并优化了用于切换螺旋桨旋转方向的时间的新变量。此外，我们建立了一种更强大的离线控制方法，通过增强目标函数来优化所需时间和最终船姿。由于此处提供的方法仍然是离线控制方法，因此其在在线控制中的适用性必须考虑外力不确定性和建模误差。然而，在这项研究中获得的最佳控制输入和轨迹集可作为在线预测控制建模的初始候选对象。此外，轨迹可以用作路径跟踪问题中的所需路径。