苏哲昊, 王伟然, 戴晓强, 等. 基于模型预测的海缆铺设用水下航行器最优避障控制[J]. 中国舰船研究, 2024, 19(1): 248–255. doi: 10.19693/j.issn.1673-3185.03125
引用本文: 苏哲昊, 王伟然, 戴晓强, 等. 基于模型预测的海缆铺设用水下航行器最优避障控制[J]. 中国舰船研究, 2024, 19(1): 248–255. doi: 10.19693/j.issn.1673-3185.03125
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SU Z H, WANG W R, DAI X Q, et al. Optimal obstacle avoidance design of autonomous underwater vehicle for cable laying based on model prediction control[J]. Chinese Journal of Ship Research, 2024, 19(1): 248–255 (in both Chinese and English). doi: 10.19693/j.issn.1673-3185.03125
Citation: SU Z H, WANG W R, DAI X Q, et al. Optimal obstacle avoidance design of autonomous underwater vehicle for cable laying based on model prediction control[J]. Chinese Journal of Ship Research, 2024, 19(1): 248–255 (in both Chinese and English). doi: 10.19693/j.issn.1673-3185.03125
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基于模型预测的海缆铺设用水下航行器最优避障控制

Optimal obstacle avoidance design of autonomous underwater vehicle for cable laying based on model prediction control

    摘要
  • 摘要:
    目的 自主水下航行器（AUV）在海底复杂地形环境下执行独立铺缆作业时，需要兼顾铺缆质量和自身安全，即在避障的同时还需要保持船体与海底平面的相对高度。为此，设计一种基于模型预测的海缆铺设AUV最优避障控制方法。
    方法 首先，基于模型预测控制（MPC）建立AUV的路径跟踪模型，将海底不规则障碍物分类为凸起和凹陷地形，并分别建立障碍物的工程简化数学模型；然后，根据不同地形和海缆铺设要求来设计多个目标优化函数；最后，根据地形特征点迭代计算与海底平面保持稳定高度且路径最短的最优避障路径。
    结果 仿真结果表明，该方法响应性能好、可靠性高，能够使AUV选择最短路径并避开意外障碍物。
    结论 在复杂的海底环境下，该方法既保障了AUV作业过程中的自身安全，又极大提高了海缆的铺设质量。

     

    Abstract:
    Objective The independent cabling operation of an autonomous underwater vehicle (AUV) in complex submarine terrain should balance cabling quality with self-safety, which means that the AUV should maintain a stable height relative to the seabed. To this end, this paper designs an optimal obstacle avoidance design for a cable-laying AUV based on model prediction control (MPC).
    Method  First, the method establishes a path-following control model based on MPC. It then classifies different obstacles into topographic bulges or depressions, and establishes a simplified mathematical model of the obstacles. Second, the method designs multiple objective optimization functions for different topographic environments according to the feature points, allowing the AUV to choose the shortest path with the minimum variation in cable-laying height.
    Results The results show that this method achieves the most minimal changes in cable-laying height while also choosing the most optimal path to avoid obstacles.
    Conclusion The proposed method not only ensures the safety of AUVs in complex submarine terrain, but also greatly improves the laying quality of submarine cables.

     

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