Please wait a minute...
 首页  期刊介绍 期刊订阅 联系我们 横山亮次奖 百年刊庆
最新录用  |  预出版  |  当期目录  |  过刊浏览  |  阅读排行  |  下载排行  |  引用排行  |  横山亮次奖  |  百年刊庆
清华大学学报(自然科学版)  2023, Vol. 63 Issue (1): 62-70    DOI: 10.16511/j.cnki.qhdxxb.2022.21.032
  机械工程 本期目录 | 过刊浏览 | 高级检索 |
吴青建1, 吴宏宇2, 江智宏1, 杨运强1, 阎绍泽2, 谭莉杰1
1. 中国地质大学(北京) 工程技术学院, 北京 100083;
2. 清华大学 机械工程系, 高端装备界面科学与技术全国重点实验室, 北京 100084
Control parameter optimization of underwater gliders for underwater fixed-point exploration missions
WU Qingjian1, WU Hongyu2, JIANG Zhihong1, YANG Yunqiang1, YAN Shaoze2, TAN Lijie1
1. School of Engineering and Technology, China University of Geosciences (Beijing), Beijing 100083, China;
2. State Key Laboratory of Tribology in Advanced Equipment, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China
全文: PDF(5374 KB)   HTML
输出: BibTeX | EndNote (RIS)      
摘要 水下滑翔机依靠净浮力和姿态调节即可实现空间运动,是一种新兴的海洋探测机器人。该文面向水下定点探测任务,开展滑翔机控制参数优化方法的研究。首先,以典型水下滑翔机为研究对象,建立了整机动力学模型,同时建立了滑翔机下潜运动的能耗模型。在此基础上,利用动力学仿真获取样本点,采用四阶多项式建立了以控制参数为输入,以滑翔机到达目标深度的能耗、运动时间和水平位移为输出的代理模型。之后,将控制参数作为优化设计变量,以最小化能耗和运动时间为优化目标,利用水平位移构造约束条件,建立优化数学模型。采用代理模型参与优化迭代计算,确保优化计算效率。最后,利用第二代非劣排序遗传算法(NSGA-II)求解上述优化问题,得到控制参数的Pareto最优解集。数值算例证明了所提出方法的正确性,可用于指导实际探测任务的控制参数配置。
E-mail Alert
关键词 水下滑翔机动力学分析水下定点探测代理模型控制参数优化    
Abstract:As a novel ocean exploration robot, an underwater glider can achieve space motion by adjusting its net buoyancy and attitude. In some exploration missions, the underwater glider must reach a specific location for virtual mooring and perform a fixed-point exploration, including the health monitoring of underwater equipment. The typical research aim is for the glider to reach the target exploration area at the earliest by consuming the minimum possible energy. To achieve this goal, the optimal control parameter configuration of the underwater glider must be determined. Therefore, this paper proposes the control parameter optimization method of underwater gliders for fixed-point exploration missions based on the dynamic theory, surrogate model technology, and multi-objective optimization algorithm. First, considering a typical underwater glider as the research object, this paper establishes the whole glider dynamic model using the Newton-Euler method. This dynamic model contains eight degrees of freedom and considers the effects of seawater density variation and hull deformation on the glider's net buoyancy. Considering the energy consumption of buoyancy adjustment, attitude adjustment, control, and measurement systems, the energy consumption model of the glider diving motion is established. On this basis, the sample points are obtained using an optimal Latin hypercube experimental design and dynamic simulation, and subsequently, the surrogate models are established using a quartic polynomial to fit the obtained sample points. Here, the input parameters of the quartic polynomial are the amounts of glider net buoyancy adjustment and movable internal mass block translation, and the output parameters are the energy consumption, diving motion time, and horizontal displacement of the glider to reach the target depth. Next, a mathematical optimization model is proposed. Specifically, the glider control parameters are selected as the optimization design variables; the optimization objective is to minimize the glider energy consumption and the diving motion time, simultaneously, and the horizontal displacement is used to construct the constraint. The surrogate models are employed to participate in the optimization calculation, which can improve the calculation efficiency. Finally, the non-dominated sorting genetic algorithm II is used to solve the abovementioned optimization problem. A numerical example is provided to validate the proposed optimization method. After optimization calculation, the Pareto optimal set is obtained, consisting of 74 sets of non-dominated solutions of control parameter values. The analysis results illustrate that once the target depth has been determined, the glider horizontal displacement shows an obvious difference under different control parameter values, implying that the glider can employ different control parameter configurations to perform underwater fixed-point exploration missions. Under a specific target depth, the quartic polynomial can accurately describe the mapping relationship among the net buoyancy adjustment amount, movable internal mass block translation amount, glider energy consumption, diving motion time, and horizontal displacement. Besides, the functional relationship between the glider control and performance evaluation parameters shows obvious nonlinearity and nonmonotonicity. Optimization results of the control parameters demonstrate a contrasting relationship between the energy consumption and the diving motion time of the glider. For practical engineering missions, the selection rule of the optimal solution is listed, and the optimization results are verified via dynamic simulation. On the basis of the dynamic theory, surrogate model technology, and multiobjective optimization algorithm, the proposed optimization method exhibits high calculation efficiency and can be used for guiding the glider control parameter configuration in actual fixed-point exploration missions. Besides, this optimization method is versatile and can be used in various types of underwater gliders.
Key wordsunderwater glider    dynamic analysis    underwater fixed-point exploration    surrogate model    control parameter optimization
收稿日期: 2022-06-18      出版日期: 2023-01-11
吴青建, 吴宏宇, 江智宏, 杨运强, 阎绍泽, 谭莉杰. 面向水下定点探测的水下滑翔机控制参数优化[J]. 清华大学学报(自然科学版), 2023, 63(1): 62-70.
WU Qingjian, WU Hongyu, JIANG Zhihong, YANG Yunqiang, YAN Shaoze, TAN Lijie. Control parameter optimization of underwater gliders for underwater fixed-point exploration missions. Journal of Tsinghua University(Science and Technology), 2023, 63(1): 62-70.
链接本文:  或
[1] STOMMEL H. The Slocum mission[J]. Oceanography, 1989, 2(1): 22-25.
[2] WEBB D C, SIMONETTI P J, JONES C P. Slocum: An underwater glider propelled by environmental energy[J]. IEEE Journal of Oceanic Engineering, 2001, 26(4): 447-452.
[3] SHERMAN J, DAVIS R E, OWENS W B, et al. The autonomous underwater glider “Spray” [J]. IEEE Journal of Oceanic Engineering, 2001, 26(4): 437-446.
[4] ERIKSEN C C, OSSE T J, LIGHT R D, et al. Seaglider: A long-range autonomous underwater vehicle for oceanographic research[J]. IEEE Journal of Oceanic Engineering, 2001, 26(4): 424-436.
[5] YU J C, ZHANG A Q, JIN W M, et al. Development and experiments of the Sea-wing underwater glider[J]. China Ocean Engineering, 2011, 25(4): 721-736.
[6] WANG S X, LI H Z, WANG Y H, et al. Dynamic modeling and motion analysis for a dual-buoyancy-driven full ocean depth glider[J]. Ocean Engineering, 2019, 187: 106163.
[7] LEONARD N E, GRAVER J G. Model-based feedback control of autonomous underwater gliders[J]. IEEE Journal of Oceanic Engineering, 2001, 26(4): 633-645.
[8] 王树新, 李晓平, 王延辉, 等. 水下滑翔器的运动建模与分析[J]. 海洋技术, 2005, 24(1): 5-9. WANG S X, LI X P, WANG Y H, et al. Dynamic modeling and analysis of underwater gliders[J]. Ocean Technology, 2005, 24(1): 5-9. (in Chinese)
[9] WANG Y H, WANG S X. Dynamic modeling and three-dimensional motion analysis of underwater gliders[J]. China Ocean Engineering, 2009, 23(3): 498-504.
[10] 王树新, 刘方, 邵帅, 等. 混合驱动水下滑翔机动力学建模与海试研究[J]. 机械工程学报, 2014, 50(2): 19-27. WANG S X, LIU F, SHAO S, et al. Dynamic modeling of hybrid underwater glider based on the theory of differential geometry and sea trails[J]. Journal of Mechanical Engineering, 2014, 50(2): 19-27. (in Chinese)
[11] YU J C, ZHANG F M, ZHANG A Q, et al. Motion parameter optimization and sensor scheduling for the Sea-wing underwater glider[J]. IEEE Journal of Oceanic Engineering, 2013, 38(2): 243-254.
[12] FAN S S, WOOLSEY C A. Dynamics of underwater gliders in currents[J]. Ocean Engineering, 2014, 84: 249-258.
[13] YOON S, KIM J. Trajectory design of underwater gliders for maximum advance speed in finite-depth water[J]. Journal of Guidance, Control, and Dynamics, 2018, 41(3): 740-748.
[14] 于鹏垚, 王天霖, 甄春博, 等. 水下滑翔机的稳态运动速度分析[J]. 哈尔滨工程大学学报, 2018, 39(11): 1767-1772. YU P Y, WANG T L, ZHEN C B, et al. Analysis of the steady-state motion velocity of an underwater glider[J]. Journal of Harbin Engineering University, 2018, 39(11): 1767-1772. (in Chinese)
[15] 顾建农, 张志宏, 王冲, 等. 海流对水下滑翔机运动参数的影响[J]. 海军工程大学学报, 2018, 30(4): 1-7, 40. GU J N, ZHANG Z H, WANG C, et al. Influence of ocean current on motion parameters of underwater glider[J]. Journal of Naval University of Engineering, 2018, 30(4): 1-7, 40. (in Chinese)
[16] NIU W D, WANG S X, WANG Y H, et al. Stability analysis of hybrid-driven underwater glider[J]. China Ocean Engineering, 2017, 31(5): 528-538.
[17] WANG S X, YANG M, WANG Y H, et al. Optimization of flight parameters for Petrel-L underwater glider[J]. IEEE Journal of Oceanic Engineering, 2021, 46(3): 817-828.
[18] WU H Y, NIU W D, WANG S X, et al. Sensitivity analysis of control parameters errors and current parameters to mot-ion accuracy of underwater glider using Sobol' method[J]. Applied Ocean Research, 2021, 110: 102625.
[19] WU H Y, NIU W D, WANG S X, et al. An optimization method for control parameters of underwater gliders considering energy consumption and motion accuracy[J]. Applied Mathematical Modelling, 2021, 90: 1099-1119.
[20] WU H Y, NIU W D, WANG S X, et al. A feedback control strategy for improving the motion accuracy of underwater gliders in currents: Performance analysis and parameter optimization[J]. Ocean Engineering, 2022, 252: 111250.
[21] YANG Y P, LIU Y H, WANG Y H, et al. Dynamic modeling and motion control strategy for deep-sea hybrid-driven underwater gliders considering hull deformation and seawater density variation[J]. Ocean Engineering, 2017, 143:66-78.
[22] 张连洪, 张宇航, 杨绍琼, 等. 一种基于低速、 小振幅周期运动CFD数值模拟的水下滑翔机附加质量求解方法[J].天津大学学报(自然科学与工程技术版), 2022, 55(3): 239-246. ZHANG L H, ZHANG Y H, YANG S Q, et al. Method for solving added mass of underwater glider based on CFD of low-speed and small-amplitude periodic motion[J]. Journal of Tianjin University(Science and Technology), 2022, 55(3): 239-246. (in Chinese)
[23] ZHANG S W, YU J C, ZHANG A Q, et al. Spiraling motion of underwater gliders: modeling, analysis, and experimental results[J]. Ocean Engineering, 2013, 60: 1-13.
[24] SONG Y, WANG Y H, YANG S Q, et al. Sensitivity analysis and parameter optimization of energy consumption for underwater gliders[J]. Energy, 2020, 191: 116506.
[1] 罗荣康, 俞志豪, 吴佩宝, 侯之超. 内悬置电动轮的柔性联轴器动力学性能分析[J]. 清华大学学报(自然科学版), 2024, 64(1): 25-32.
[2] 耿俊杰, 王兴建, 李嘉璐, 费腾, 祁海鹰. 燃烧室流动混合过程的代理模型[J]. 清华大学学报(自然科学版), 2023, 63(4): 633-641.
[3] 刘哲, 金达锋, 范志瑞. 基于代理模型的复合材料带加强筋板铺层优化[J]. 清华大学学报(自然科学版), 2015, 55(7): 782-789.
Full text



版权所有 © 《清华大学学报(自然科学版)》编辑部
本系统由北京玛格泰克科技发展有限公司设计开发 技术支持