This paper presents the formulation of a flocking control algorithm for a group of autonomous underwater vehicles (AUVs). A leader–follower control strategy is employed to flock a group of AUVs along a predefined desired path. In this approach, leader AUVs are assumed to have global knowledge of the desired trajectory and the follower AUVs are not provided with this information. For keeping all the AUVs connected in a group, a flocking center is estimated. This flocking center is a virtual point whose position at any instant of time can be predicted by using a consensus algorithm. The controllers for the leader and follower AUVs are developed by implementing mathematical and fuzzy artificial potential functions. A group of four AUVs is considered for analyzing the efficacy of the developed control algorithm. Simulations are carried out both in obstacle-free and obstacle-rich environments. From the obtained results, it is observed that the proposed fuzzy flocking control algorithm provides effective cooperative motion control of multiple AUVs along the desired paths and avoid obstacles successively. It is also observed that the flocking controller developed based on fuzzy artificial potential function outperforms the controller with mathematical potential functions despite uncertainties owing to external disturbances.

中文翻译：

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基于模糊势函数的多台AUV集群控制

本文介绍了一组自主水下航行器 (AUV) 的群集控制算法的制定。领导者-跟随者控制策略用于沿着预定义的所需路径聚集一组 AUV。在这种方法中，假设领导 AUV 具有所需轨迹的全局知识，而跟随 AUV 不提供此信息。为了将所有 AUV 保持在一个组中，估计了一个群集中心。该集群中心是一个虚拟点，其在任何时刻的位置都可以通过共识算法进行预测。领导者和跟随者 AUV 的控制器是通过实现数学和模糊人工势函数来开发的。一组四个 AUV 被考虑用于分析开发的控制算法的功效。模拟在无障碍和障碍丰富的环境中进行。从获得的结果可以看出，所提出的模糊群集控制算法提供了多个 AUV 沿所需路径的有效协同运动控制，并依次避开障碍物。还观察到，尽管由于外部干扰存在不确定性，但基于模糊人工势函数开发的植绒控制器优于具有数学势函数的控制器。