贾金恒, 黄琰, 赵文涛, 等. 基于模型预测控制的无人帆船轨迹跟踪方法[J]. 中国舰船研究, 2024, 19(1): 145–157. doi: 10.19693/j.issn.1673-3185.03162
引用本文: 贾金恒, 黄琰, 赵文涛, 等. 基于模型预测控制的无人帆船轨迹跟踪方法[J]. 中国舰船研究, 2024, 19(1): 145–157. doi: 10.19693/j.issn.1673-3185.03162
JIA J H, HUANG Y, ZHAO W T, et al. Unmanned sailboat trajectory tracking method based on model predictive control[J]. Chinese Journal of Ship Research, 2024, 19(1): 145–157 (in Chinese. doi: 10.19693/j.issn.1673-3185.03162
Citation: JIA J H, HUANG Y, ZHAO W T, et al. Unmanned sailboat trajectory tracking method based on model predictive control[J]. Chinese Journal of Ship Research, 2024, 19(1): 145–157 (in Chinese. doi: 10.19693/j.issn.1673-3185.03162

基于模型预测控制的无人帆船轨迹跟踪方法

Unmanned sailboat trajectory tracking method based on model predictive control

  • 摘要:
    目的 面向无人帆船在水面、水下跨域异构海洋机器人的协同作业场景,提出基于模型预测控制(MPC)的无人帆船轨迹跟踪方法。
    方法 针对“海鸥”号无人帆船,建立其动力学模型及运动学模型,通过分析无人帆船动力学特点及执行器约束条件,构建MPC目标函数及系统约束条件,将无人帆船的轨迹跟踪问题转化为优化问题,并利用Matlab软件开展仿真实验验证。
    结果 仿真结果表明,与“帆–舵”分离的PID轨迹跟踪控制方法相比,所提出的无人帆船“帆–舵”联合MPC控制方法更便于添加约束条件,其在风向变化的情况下能以更小的轨迹跟踪误差来更快地收敛于指定轨迹,且其可以实现逆风折线行驶。
    结论 研究成果可为无人帆船的帆、舵控制提供新的思路,提高其轨迹跟踪能力,进一步为无人帆船与AUV的高效协同作业提供技术保障。

     

    Abstract:
    Objective An unmanned sailboat trajectory tracking method based on model predictive control (MPC) is proposed for the collaborative operation of unmanned sailboats in surface/underwater cross-domain heterogeneous marine robotics scenarios.
    Methods Using the unmanned sailboat Seagull, we establish its dynamics and kinematics models, analyze its dynamic characteristics and actuator constraints, construct the MPC objective function and system constraints, convert the trajectory tracking problem of the unmanned sailboat into an optimization problem and carry out simulation and experimental validation using Matlab software.
    Results The simulation results show that compared with the sail-rudder separate PID trajectory tracking control method, the proposed sail-rudder joint MPC control method is more convenient for adding constraints. It can converge to the specified trajectory faster with smaller trajectory tracking error under a changing wind direction and realize upwind zigzag sailing.
    Conclusions The results of this study can provide new ideas for the sail and rudder control of unmanned sailboats, improve the trajectory tracking ability and provide a further technical guarantee for the efficient collaborative operation of unmanned sailboats and AUVs.

     

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