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Co-operative control coordination of a team of underwater vehicles with communication constraints

机译:具有通信约束的水下机器人团队的协同控制协调

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摘要

Co-operative control architectures for implementation of motion plan and coordination strategies for a team of Autonomous Underwater Vehicles (AUVs) using different optimization techniques are presented in this paper. The paper addresses the leader-follower formation control of multiple non-holonomic AUVs where one AUV is designated as Leader and the other participating AUVs are treated as the followers. In this scenario, the leader operates according to its optimized path, while each follower is required to follow the leader accurately maintaining desired separations and orientation with respect to the leader. A communication strategy is also designed so that the AUVs can exchange information to obtain the designated waypoints that are sent from the leader following the area coverage problem. Optimization is necessary to determine the optimal path as functions of sensor nodes for control coordination of a team of AUVs satisfying the time minimization. Various optimization algorithms have been employed for control coordination and search strategies of co-operative motion control of a group of AUVs without incorporating learning and memory to evaluate the objective function. The CLONAL selection algorithm is found to be one of the best approaches to plan the formation leader motion utilizing the triangular sensor-based grid coverage technique. The efficacy of the proposed optimization approach to solve the co-operation motion of a group of AUVs is verified through MATLAB simulation studies and the results confirmed the robustness and efficiency of the proposed technique over existing search methodologies, such as Coordinate, Multi-directional, Simplex and Simultaneous Perturbation Stochastic Approximation.
机译:本文介绍了使用不同的优化技术为一组自主水下航行器(AUV)实施运动计划和协调策略的协作控制体系结构。本文讨论了多个非完整AUV的领导者跟随者形成控制,其中一个AUV被指定为领导者,而其他参与的AUV被视为跟随者。在这种情况下,领导者将根据其优化的路径进行操作,而每个跟随者都需要精确地跟随领导者,并保持相对于领导者的期望间隔和方向。还设计了一种通信策略,以便AUV可以交换信息以获得在区域覆盖问题后从领导者发送的指定航点。需要进行优化以确定作为传感器节点功能的最佳路径,以实现满足时间最小化的AUV团队的控制协调。在不结合学习和记忆来评估目标功能的情况下,已将各种优化算法用于一组AUV的协同运动控制的控制协调和搜索策略。发现CLONAL选择算法是利用基于三角形传感器的网格覆盖技术来计划编队领导运动的最佳方法之一。通过MATLAB仿真研究验证了所提出的优化方法解决一组AUV的协同运动的有效性,结果证实了所提出技术在现有搜索方法(例如坐标,多向,单纯形和同时摄动随机逼近。

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