输入约束下的浮力调节式UUV变深控制

doi:10.12305/j.issn.1001-506X.2022.11.25

系统工程与电子技术 ›› 2022, Vol. 44 ›› Issue (11): 3496-3504.doi: 10.12305/j.issn.1001-506X.2022.11.25

输入约束下的浮力调节式UUV变深控制

徐海祥^1,², 胡聪^1,², 余文曌^1,^2,*, 姚国全^1,²

1. 武汉理工大学高性能舰船技术教育部重点实验室, 湖北武汉 430063
2. 武汉理工大学船海与能源动力工程学院, 湖北武汉 430063

收稿日期:2021-10-21 出版日期:2022-10-26 发布日期:2022-10-29
通讯作者: 余文曌
作者简介:徐海祥(1975—), 男, 教授, 博士, 主要研究方向为海洋智能装备技术|胡聪(1996—), 男, 硕士研究生, 主要研究方向为无人水下航行运动控制|余文曌(1989—), 男, 讲师, 博士, 主要研究方向为海洋智能装备控制技术|姚国全(1989—), 男, 实验员, 博士研究生, 主要研究方向为海洋智能装备水动力数值计算
基金资助:
国家自然科学基金(51879210);国家自然科学基金(51979210);中央高校基本科研业务费专项资金(2019III040);中央高校基本科研业务费专项资金(2019III132CG)

Variable depth control of buoyancy regulated UUV with input constraints

Haixiang XU^1,², Cong HU^1,², Wenzhao YU^1,^2,*, Guoquan YAO^1,²

1. Key Laboratory of High Performance Ship Technology, Ministry of Education, Wuhan University of Technology, Wuhan 430063, China
2. School of Naval Architecture, Ocean and Energy Power Engineering, Wuhan University of Technology, Wuhan 430063, China

Received:2021-10-21 Online:2022-10-26 Published:2022-10-29
Contact: Wenzhao YU

摘要/Abstract

摘要：

针对浮力调节机构约束下无人水下航行器(unmanned underwater vehicle, UUV)的变深控制问题, 提出一种基于正交神经网络饱和补偿器的自适应动态面控制方法。首先，建立考虑执行机构动态特性的UUV数学模型。在此基础上, 采用反步法和非线性跟踪微分器设计动态面控制器, 同时引入线性扩张状态观测器(linear extended state observer, LESO)在线估计浮力变化与模型不确定性引起的干扰, 继而在控制器中进行补偿。然后，基于正交神经网络设计饱和补偿器, 并证明闭环系统所有误差一致最终有界。仿真结果表明, 与现有的动态面控制方法相比, 所提方法在浮力调节机构约束下, 具有较好的动态性能与稳态精度。

关键词: 浮力调节机构, 无人水下航行器, 动态面控制器, 线性扩张状态观测器, 正交神经网络饱和补偿器

Abstract:

Aiming at the problem of variable depth control of unmanned underwater vehicle(UUV) constrained by the buoyancy regulator mechanism, an adaptive dynamic surface control method based on the orthogonal neural network saturation compensator is proposed. Firstly, the UUV mathematical model considering the dynamic characteristics of the actuator is established. On this basis, the dynamic surface controller is designed by using the backstepping method and the nonlinear tracking differentiator. The linear extended state observer (LESO) is designed to estimate the disturbance caused by buoyancy change and model uncertainty online. Then compensation is carried out in the controller. Secondly, the saturation compensator is designed based on the orthogonal neural network. It is proved that all the errors of the closed-loop system are consistent and finally bounded. The simulation results show that the proposed method has better dynamic performance and steady-state precision under the constraint of the buoyancy regulator mechanism compared with the existing dynamic surface control method.

Key words: buoyancy regulator, unmanned underwater vehicle (UUV), dynamic surface controller, linear extended state observer (LESO), orthogonal neural network saturation compensator

中图分类号:

TP273

徐海祥, 胡聪, 余文曌, 姚国全. 输入约束下的浮力调节式UUV变深控制[J]. 系统工程与电子技术, 2022, 44(11): 3496-3504.

Haixiang XU, Cong HU, Wenzhao YU, Guoquan YAO. Variable depth control of buoyancy regulated UUV with input constraints[J]. Systems Engineering and Electronics, 2022, 44(11): 3496-3504.

图/表 8

图1

图2

图3

图4

图5

图6

图7

图8

参考文献 31

1	MELO J , MATOS A . Survey on advances on terrain based navigation for autonomous underwater vehicles[J]. Ocean Engineering, 2017, 139, 250- 264. doi: 10.1016/j.oceaneng.2017.04.047
2	BUDIYONO A . Advances in unmanned underwater vehicles technologies: modeling, control and guidance perspectives[J]. Indian Journal of Geo-Marine Sciences, 2009, 38 (3): 282- 295.
3	王佳. AUV浮力调节系统设计及控制策略研究[D]. 天津: 天津大学, 2017.
	WANG J. Design of the variable buoyancy system of AUV and research of the control strategy[D]. Tianjin: Tianjin University, 2017.
4	CHEN T , ZHU M , ZHENG Z W . Asymmetric error-constrained path-following control of a stratospheric airship with distur-bances and actuator saturation[J]. Mechanical Systems and Signal Processing, 2019, 119, 501- 522. doi: 10.1016/j.ymssp.2018.10.003
5	张勋, 边信黔, 唐照东. AUV均衡系统设计及垂直面运动控制研究[J]. 中国造船, 2012, 53 (1): 28- 36.
	ZHANG X , BIAN X Q , TANG Z D , et al. Design of balance system for AUV and study on motion control in vertical plane[J]. Shipbuilding of China, 2012, 53 (1): 28- 36.
6	SYLVESTER A H, DELMERICO J A, TRIMNLE A Z, et al. Variable buoyancy control for a bottom skimming autonomous underwater vehicle[C]//Proc. of the IEEE Oceans-St. John's, 2014.
7	王雨, 郑荣, 武建国. 基于浮力调节系统的AUV深度控制研究[J]. 自动化与仪表, 2015, 30 (4): 6- 10. doi: 10.3969/j.issn.1001-9944.2015.04.002
	WANG Y , ZHENG R , WU J G . Research on AUV depth control based on the variable buoyancy system[J]. Process Automation Instrumentation, 2015, 30 (4): 6- 10. doi: 10.3969/j.issn.1001-9944.2015.04.002
8	孙庆刚, 郑荣, 安家玉. 基于浮力调节系统的AUV定深悬浮控制[J]. 海洋技术学报, 2017, 36 (6): 33- 37.
	SUN Q G , ZHENG R , AN J Y , et al. Study on the AUV depth and hovering control based on variable buoyancy system[J]. Ocean Technology, 2017, 36 (6): 33- 37.
9	ZAVISLAK C , KEOW A , CHEN Z , et al. AUV buoyancy control with hard and soft actuators[J]. IEEE Control Systems Letters, 2020, 5 (6): 1874- 1879.
10	TIWARI B K , SHARMA R . Design and analysis of a variable buoyancy system for efficient hovering control of underwater vehicles with state feedback controller[J]. Journal of Marine Science and Engineering, 2020, 8 (4): 263. doi: 10.3390/jmse8040263
11	SUN Y C , DU Y T , QIN H D . Distributed adaptive neural network constraint containment control for the benthic autonomous underwater vehicles[J]. Neurocomputing, 2022, 484, 89- 98. doi: 10.1016/j.neucom.2021.03.137
12	TARBOURIECH S , TURNER M . Anti-windup design: an overview of some recent advances and open problems[J]. IET Control Theory & Applications, 2009, 3 (1): 1- 19.
13	WANG S Y , GAO Y B , LIU J X , et al. Saturated sliding mode control with limited magnitude and rate[J]. IET Control Theory & Applications, 2018, 12 (8): 1075- 1085.
14	SHAMMA J S . Anti-windup via constrained regulation with observers[J]. Systems & Control Letters, 2000, 40 (4): 261- 268.
15	RICHTER S , NEIL C N , MORARI M . Computational complexity certification for real-time MPC with input constraints based on the fast gradient method[J]. IEEE Trans.on Automatic Control, 2012, 57 (99): 1391- 1403.
16	JIANG Y , ORAVEC J , HOUSKA B , et al. Parallel MPC for linear systems with input constraints[J]. IEEE Trans.on Automatic Control, 2020, 66 (7): 3401- 3408.
17	MAZENC F , MALISOFF M , BURLION L , et al. Bounded backstepping control and robustness analysis for time-varying systems under converging-input-converging-state conditions[J]. European Journal of Control, 2018, 42, 15- 24.
18	PRIANDIRI V P, MARHAM Q C, TRILAKSONO B R, et al. Control system for simplified nonlinear dynamic model of 6 DOF hybrid underwater glider using PID controller with anti-windup[C]//Proc. of the IEEE 9th International Conference on System Engineering and Technology, 2019: 50-55.
19	WU N L, LIU Z L, WU C, et al. Robust MRAC with anti-windup compensator for the depth channel of an autonomous underwater vehicle[C]//Proc. of the 28th International Ocean and Polar Engineering Conference, 2018.
20	CUI R X , ZHANG X , CUI D . Adaptive sliding-mode attitude control for autonomous underwater vehicles with input nonli-nearities[J]. Ocean Engineering, 2016, 123, 45- 54.
21	NGUYEN A T , DAMBRINE M , LAUBER J . Simultaneous design of parallel distributed output feedback and anti-windup compensators for constrained Takagi-Sugeno fuzzy systems[J]. Asian Journal of Control, 2016, 18 (5): 1641- 1654.
22	ZHENG C B, WU X Y, HUANG C Q. Two step approach for robust anti-windup design[C]//Proc. of the IEEE International Conference on Advanced Mechatronic Systems, 2017.
23	TANAKITKORN K , WILSON P A , TURNOCK S R , et al. Depth control for an over-actuated, hover-capable autonomous underwater vehicle with experimental verification[J]. Mechatronics, 2017, 41, 67- 81.
24	CHEN T, ZHANG W, ZHOU J J, et al. Depth control of AUV using active disturbance rejection controller[C]//Proc. of the IEEE 33rd Chinese Control Conference, 2014: 7948-7952.
25	YU W Z , XU H X , HAN X , et al. Fault-tolerant control for dynamic positioning vessel with thruster faults based on the neural modified extended state observer[J]. IEEE Trans.on Systems, Man, and Cybernetics: Systems, 2019, 51 (9): 5905- 5917.
26	谭诗利, 雷虎民, 王鹏飞. 基于正切Sigmoid函数的跟踪微分器[J]. 系统工程与电子技术, 2019, 41 (7): 1590- 1596.
	TAN S L , LEI H M , WANG P F . Design of tracking differentiator based on tangent Sigmoid function[J]. Systems Engineering and Electronics, 2019, 41 (7): 1590- 1596.
27	QU Y , XU H X , YU W Z , et al. Inverse optimal control for speed-varying path following of marine vessels with actuator dynamics[J]. Journal of Marine Science and Application, 2017, 16 (2): 225- 236.
28	GAO W , SELMIC R R . Neural network control of a class of nonlinear systems with actuator saturation[J]. IEEE Trans.on Neural Networks, 2006, 17 (1): 147- 156.
29	郭晓丽, 方建印. Lyapunov稳定性逆定理的另一种证明[J]. 郑州大学学报(理学版), 2004, (2): 22- 24.
	GUO X L , FANG J Y . Another proof of the converse Lyapunov stability theorem[J]. Journal of Zhengzhou University(Natural Science Edition), 2004, (2): 22- 24.
30	QU Y , XU H X , YU W Z , et al. Inverse optimal control for speed-varying path following of marine vessels with actuator dynamics[J]. Journal of Marine Science and Application, 2017, 16 (2): 225- 236.
31	徐海祥, 胡聪, 余文曌, 等. 基于LESO无人水下航行器鲁棒动态面悬停控制[J]. 华中科技大学学报(自然科学版), 2021, 49 (8): 98- 103.98-103, 126
	XU H X , HU C , YU W Z , et al. Robust dynamic surface controller for hovering control of unmanned underwater vehicle based on LESO[J]. Journal of Huazhong University of Science and Technology (Natural Science Edition), 2021, 49 (8): 98- 103.98-103, 126

[1]	韦俊宝, 李海燕, 李静. 高超声速飞行器新型攻角约束反演控制[J]. 系统工程与电子技术, 2022, 44(4): 1310-1317.
[2]	曹晓明, 魏勇, 衡辉, 沈智鹏. 海流扰动下无人水下航行器的动态面反演轨迹跟踪控制[J]. 系统工程与电子技术, 2021, 43(6): 1664-1672.
[3]	张银辉, 杨华波, 江振宇, 张为华. 基于干扰估计的高超声速飞行器鲁棒控制方法[J]. 系统工程与电子技术, 2016, 38(4): 875-881.
[4]	李向阳. 基于等效控制的迭代学习控制[J]. 系统工程与电子技术, 2014, 36(7): 1397-1404.
[5]	陈盼，吴晓锋. UUV编队协同最优扩方应召搜索方法[J]. Journal of Systems Engineering and Electronics, 2013, 35(5): 987-992.
[6]	陈盼, 吴晓锋, 陈云. UUV编队协同应召搜索马尔可夫运动目标的方法[J]. Journal of Systems Engineering and Electronics, 2012, 34(8): 1630-1634.

输入约束下的浮力调节式UUV变深控制

Variable depth control of buoyancy regulated UUV with input constraints

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 8

参考文献 31

相关文章 6

编辑推荐

Metrics

本文评价