Among the promising application of autonomous surface vessels (ASVs) is the utilization of multiple autonomous tugs for manipulating a floating object such as an oil platform, a broken ship, or a ship in port areas. Considering the real conditions and operations of maritime practice, this paper proposes a multi-agent control algorithm to manipulate a ship to a desired position with a desired heading and velocity under the environmental disturbances. The control architecture consists of a supervisory controller in the higher layer and tug controllers in the lower layer. The supervisory controller allocates the towing forces and angles between the tugs and the ship by minimizing the error in the position and velocity of the ship. The weight coefficients in the cost function are designed to be adaptive to guarantee that the towing system functions well under environmental disturbances, and to enhance the efficiency of the towing system. The tug controller provides the forces to tow the ship and tracks the reference trajectory that is computed online based on the towing angles calculated by the supervisory controller. Simulation results show that the proposed algorithm can make the two autonomous tugs cooperatively tow a ship to a desired position with a desired heading and velocity under the (even harsh) environmental disturbances.

中文翻译：

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环境干扰下自主船舶拖曳的多智能体协作控制


自主水面舰艇（ASV）最有前途的应用之一是利用多个自主拖船来操纵浮动物体，例如石油平台、破损的船舶或港口区域的船舶。考虑到海上实践的实际情况和操作，本文提出了一种多智能体控制算法，可以在环境扰动下以期望的航向和速度操纵船舶到达期望的位置。控制架构由上层的监控控制器和下层的拖船控制器组成。监控控制器通过最小化船舶位置和速度的误差来分配拖船和船舶之间的拖曳力和角度。成本函数中的权重系数被设计成自适应的，以保证拖曳系统在环境扰动下良好运行，并提高拖曳系统的效率。拖船控制器提供拖曳船舶的力，并跟踪根据监控控制器计算的拖曳角度在线计算的参考轨迹。仿真结果表明，所提出的算法可以使两个自主拖船在（甚至恶劣的）环境干扰下以期望的航向和速度协同地将船舶拖曳到期望的位置。