首页> 外文期刊>Proceedings of the Institute of Marine Engineering, Science and Technology >Co-operative control of a team of autonomous underwater vehicles in an obstacle-rich environment
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Co-operative control of a team of autonomous underwater vehicles in an obstacle-rich environment

机译:在充满障碍的环境中对一组自动水下机器人的协同控制

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摘要

This paper presents the cooperative control of a team of autonomous underwater vehicles (AUVs) in the presence of obstacles under environmental disturbance. A leader-follower formation control based on optimisation algorithms using communication topology is designed to navigate towards the target in the presence of obstacles. CLONAL selection optimisation algorithm may be employed as team controller by providing the optimal position to hierarchical control strategy for each AUV incorporating learning, memory and affinity. But unfortunately CLONAL selection optimisation algorithm fails to avoid obstacles because some of the lymphocytes become memory cells of the system. The above prematurity may be overcome by using artificial potential fields and ant colony optimisation technique combined with CLONAL selection optimisation algorithm. The efficacy of the proposed optimisation is verified through MATLAB simulation and the result confirmed the robustness and proficiency of proposed technique over CLONAL selection optimisation algorithm.
机译:本文提出了在环境干扰下存在障碍物的情况下,一组无人水下航行器(AUV)的协同控制。基于使用通信拓扑的优化算法的前随从编队控制被设计为在存在障碍物的情况下向目标导航。通过为结合学习,记忆和亲和力的每​​个AUV提供最佳位置给分层控制策略,可以将CLONAL选择优化算法用作团队控制器。但是不幸的是,CLONAL选择优化算法无法避免障碍,因为某些淋巴细胞成为系统的记忆细胞。可以通过使用人工势场和蚁群优化技术结合CLONAL选择优化算法来克服上述早熟问题。通过MATLAB仿真验证了所提优化算法的有效性,结果证实了所提技术优于CLONAL选择优化算法的鲁棒性和熟练度。

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