结合ILOS及IPID-GWO的无人水翼航行器路径跟踪优化

毕成; 段富海

doi:10.11993/j.issn.2096-3920.2024-0177

结合ILOS及IPID-GWO的无人水翼航行器路径跟踪优化

doi: 10.11993/j.issn.2096-3920.2024-0177

毕成,
段富海

大连理工大学机械工程学院, 辽宁大连, 116024

详细信息

作者简介:
毕成：毕　成(1999-), 男, 在读硕士, 主要研究方向为无人水翼航行器路径跟踪控制

中图分类号: TJ630; U674.941
计量
- 文章访问数: 19
- HTML全文浏览量: 4
- PDF下载量: 5
- 被引次数: 0
出版历程
- 收稿日期: 2024-12-23
- 修回日期: 2025-01-19
- 录用日期: 2025-02-08
- 网络出版日期: 2025-07-18

Path Tracking Optimization for Unmanned Hydrofoil Vehicle Based on ILOS and IPID-GWO

School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China

摘要

摘要: 为解决新型无人水翼航行器的路径跟踪问题, 提出了一种基于视线制导法(LOS)并结合增量式比例-积分-微分控制器(IPID)的跟踪策略。首先, 建立了航行器的3自由度运动学和动力学模型, 并通过控制策略实现控制输入解耦; 结合可变前视距离与积分项改进了LOS制导法, 得到ILOS算法; IPID控制器使用ILOS算法得到的期望航向角进行跟踪过程的动态控制, 同时在算法中增加跟踪点切换时的补偿输入, 避免了因剧烈变化导致的系统失控; 分别使用灰狼优化算法(GWO)与遗传算法(GA)对IPID控制器的权重系数进行优化和对比。在Matlab中使用ILOS及IPID控制器对给定的直线-曲线混合路径在无干扰与有干扰时进行路径跟踪仿真, 通过分析跟踪效果和横向误差, 验证了ILOS和IPID-GWO算法结合的可行性和先进性。
- 无人水翼航行器 /
- 路径跟踪 /
- 视线制导法 /
- 增量式比例-积分-微分控制器 /
- 灰狼优化算法
Abstract: In order to solve the path tracking problem of a new type of unmanned hydrofoil vehicle, a tracking strategy based on line of sight(LOS) guidance combined with an incremental proportional-integral-differential(IPID) controller was proposed. Firstly, the 3-DOF kinematic and dynamic models of the vehicle were established, and the control input was decoupled through the control strategy. The LOS guidance method was improved by combining the variable foresight distance and integral term, and the ILOS algorithm was obtained. The IPID controller used the desired heading angle obtained by the ILOS algorithm to dynamically control the tracking process. The compensation input when switching the tracking point was added to the algorithm to avoid the system’s out-of-control problem caused by excessive changes. The weight coefficients in the IPID controller were optimized and compared using the grey wolf optimizer(GWO) algorithm and genetic algorithm(GA). In Matlab, the ILOS and IPID controllers were used to track the given straight and curved mixed path in the absence and presence of interference. The tracking effect and lateral error were analyzed, and the feasibility and advancement of the combination of ILOS and IPID-GWO algorithms were verified.
- unmanned hydrofoil vehicle /
- path tracking /
- line-of-sight guidance method /
- incremental proportional-integral-differential controller /
- grey wolf optimizer

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图 1 无人水翼航行器三维模型

Figure 1. Three dimensional model of an unmanned hydrofoil vehicle

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图 2 传统LOS制导算法

Figure 2. Traditional LOS guidance algorithm

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图 3 ILOS+IPID-GWO路径跟踪控制结构

Figure 3. Path tracking control structure of ILOS guidance combined with IPID-GWO

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图 4 无干扰时路径跟踪效果对比图

Figure 4. Comparison of path tracking effects when there is no interference

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图 5 有干扰时路径跟踪效果对比图

Figure 5. Comparison of path tracking effect when there is interference

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表 1 无人水翼航行器建模参数及公式

Table 1. Modeling parameters and formulas of unmanned hydrofoil vehicles

参数	取值/公式	参数	取值/公式
$ m $	53.89	$ {x_g} $	0
$ {X_{\dot u}} $	−2.29	$ {Y_{\dot v}} $	−13.71
$ {Y_{\dot r}} $	2.23	$ {N_{\dot v}} $	2.23
$ {I_{\textit{z}}} $	8.71	$ {N_{\dot r}} $	3.19
$ b $	0.48	$ L $	0.8
$ {d_{11}} $	$ 2.29 + 1.33\left\| u \right\| $	$ {d_{22}} $	$ 13.71 + 36.47\left\| v \right\| + 0.81\left\| r \right\| $
$ {d_{23}} $	$ - 2.23 + 0.85\left\| v \right\| - 0.13\left\| r \right\| $	$ {d_{32}} $	$ - 2.23 + 0.85\left\| v \right\| - 0.13\left\| r \right\| $
$ {d_{33}} $	$ - 3.19 - 0.08\left\| v \right\| + 0.75\left\| r \right\| $

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表 2 仿真结果数据

Table 2. Simulation result data

	跟踪时间/s		$ {y_e} $绝对值和				$ u $方差
	无干扰	有干扰	无干扰	有干扰	部分直线-无干扰	部分直线-有干扰	部分直线-无干扰	部分直线-有干扰
LOS+IPID	400.5	407.9	2 746.4	7 583.1	10.914 4	563.794 7	0.002 058	0.034 333
ILOS+IPID	404.2	415.0	2 694.0	5 903.0	30.240 5	397.614 7	0.012 211	0.092 868
ILOS+IPID-GA	403.8	410.2	2 685.4	4 826.3	30.520 6	308.041 4	0.008 972	0.044 648
ILOS+IPID-GWO	406.3	408.6	2 536.5	3 760.9	25.458 2	197.470 7	0.003 199	0.018 585

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