水下移动机器人运动控制系统的设计和实现

水下机器人在执行任务过程中要求有稳定可靠的运动控制系统和控制算法使其能够保持自身深度和姿态的稳定并快速切换到目标深度及姿态。经过对现有水下机器人控制技术的调研以及前人的研究分析，总结出两个可改进之处：（1）目前大多数水下机器人只能控制深度和一到两个姿态角，没有对深度和三轴姿态角（横滚角，纵倾角，艏向角）进行联合控制；（2）针对深度和姿态角控制任务，工程应用中经典 PID 算法应用最为广泛，但控制性能如快速性和稳定性有待改进。基于此设计了一种新型水下移动机器人，并设计其运动控制系统和控制算法，进行深度和三轴姿态角联合控制。

设计了水下移动机器人结构，接着针对深度和三轴姿态角联合控制任务，建立了控制水下移动机器人深度和三轴姿态角的数学模型完成模型简化。构建了水下移动机器人运动控制系统，架构从上到下为上位机、伴随机和下位机。通过对现有控制算法分析，研究了串级 PID 和自抗扰控制两种控制算法。基于这两种控制算法设计了水下移动机器人深度和姿态控制器，对深度和三轴姿态角进行联合调节控制，并对各部分参数进行介绍及整定。

在 Matlab 仿真环境中通过静态无干扰跟踪和动态带干扰跟踪实验验证了这两种控制算法的可行性、快速性和抗干扰性。在水池实验环境中通过与经典 PID 控制算法对比，验证了运动控制系统的实用性、稳定性和可靠性，并证明串级 PID 和自抗扰控制两种控制算法的可行性和有效性以及在快速性及稳定性方面都优于经典 PID 控制算法。

The underwater robot needs a stable and reliable motion control system and control algorithm to keep its depth and attitude stable and quickly switch to the target depth and attitude during the execution of the task. Through the research and analysis of the existing control technology of underwater robots and the previous research and analysis, two improvements are summarized: (1) At present, most underwater robots can only control the depth and one or two attitude angles, and there is no joint control of the depth and three-axis attitude angles(roll, pitch, and yaw); (2) For depth and attitude angles control tasks, the classical PID algorithm is the most widely used in engineering applications, but the control performance such as rapidity and stability need to be improved. Based on this, a new type of underwater mobile robot is designed, its motion control system and control algorithm are designed, and the depth and three-axis attitude angles are controlled jointly.
The structure of the underwater mobile robot is designed, and then the mathematical
model of controlling the depth and three-axis attitude angles of the underwater mobile robot is established to simplify the model. The motion control system of underwater mobile robot is constructed, which is composed of upper computer, companion computer and lower computer from top to bottom. By analyzing the existing control algorithms, two control algorithms cascade PID and ADRC are studied. Based on this, depth and attitude controllers of underwater mobile robots are designed respectively, which can jointly adjust and control depth and attitude angles, and introduce and adjust the parameters of each part.
The feasibility, rapidity and anti-interference of these two control algorithms are verified by the experiments of static non-interference tracking and dynamic tracking with interference in Matlab simulation environment. The practicability, stability and reliability of the motion control system are verified by comparing with the classical PID control algorithm in the experimental environment of the pool, and the feasibility and effectiveness of cascade PID and ADRC are proved to be superior to the classical PID control algorithm in terms of rapidity and stability.

[1] 楼东, 谷树忠, 钟赛香. 中国海洋资源现状及海洋产业发展趋势分析[J]. 资源科学, 2005(5): 20-26.
[2] 韦荣伟. 水下机器人发展趋势及前景[J]. 现代制造技术与装备, 2018(2): 175-176.
[3] 徐会希, 姜成林. 基于 USV 与 AUV 异构平台协同海洋探测系统研究综述（英文）[J]. 中国科学院大学学报, 2021, 38(2): 145-159.
[4] TEAGUE J, ALLEN M J, SCOTT T B. The potential of low-cost ROV for use in deep-sea mineral, ore prospecting and monitoring[J]. Ocean Engineering, 2018, 147(1): 333-339.
[5] 曹少华, 张春晓, 王广洲, 等. 智能水下机器人的发展现状及在军事上的应用[J]. 船舶工程, 2019, 41(2): 79-84+89.
[6] NEIRA J, SEQUEIROS C, HUAMANI R, et al. Review on unmanned underwater robotics,structure designs, materials, sensors, actuators, and navigation control[J]. Journal of Robotics,2021, 2021: 5542920.
[7] 李硕, 刘健, 徐会希, 等. 我国深海自主水下机器人的研究现状[J]. 中国科学: 信息科学,2018, 48(9): 1152-1164.
[8] ZHANG Y, ZHANG Q, ZHANG A, et al. Development and experiments of a novel deep-sea resident ROV[C]//2021 6th International Conference on Control and Robotics Engineering(ICCRE). IEEE, 2021: 129-134.
[9] CHRIST R D, WERNLI SR R L. The ROV manual: a user guide for remotely operated vehicles[M]. Butterworth-Heinemann, 2013: 10-20.
[10] 商承超, 王伟, 谢广明, 等. 水下机器人定位方法综述[J]. 兵工自动化, 2013, 32(12): 46-50.
[11] 刘甜甜, 秦峰, 朱晓勇, 等. 水下自主导航机器人系统[J]. 兵工自动化, 2012, 31(11): 66-72.
[12] 刘赫, 高兴, 张成刚, 等. 具有水样采集功能的观测型水下机器人的设计[J]. 吉林大学学报(信息科学版), 2020, 38(6): 737-743.
[13] AMRAN I Y, ISA K, KADIR H A, et al. Development of autonomous underwater vehicle for water quality measurement application[C]//National Technical Seminar on Unmanned System Technology. Springer, 2019: 139-161.
[14] YANG X, WU Z, YU J. Design and implementation of a robotic shark with a novel embedded vision system[C]//2016 IEEE International Conference on Robotics and Biomimetics (ROBIO).IEEE, 2016: 841-846.
[15] 林兴华, 武建国, 秦青, 等. 水下机器人基于侧线机理对目标感知方法的研究[J]. 船舶力学, 2020, 24(5): 559-569.
[16] SIVČEV S, COLEMAN J, OMERDIĆ E, et al. Underwater manipulators: a review[J]. OceanEngineering, 2018, 163(17): 431-450.
[17] 徐杨. 海生物抓取捕捞水下机器人运动规划研究[D]. 哈尔滨工程大学, 2020: 10-20.
[18] CHUTIA S, KAKOTY N M, DEKA D. A review of underwater robotics, navigation, sens￾ing techniques and applications[C]//Proceedings of the 2017 3rd International Conference on Advances in Robotics. 2017: 1-6.
[19] 王雷. 水下机器人运动控制研究[D]. 中国科学技术大学, 2018: 11-22.
[20] GÓMEZ Á, ARISTIZÁBAL L M, ZULUAGA C A, et al. Development and implementation of a high-level control system for the underwater remotely operated vehicle Visor3[J]. IFAC-PapersOnLine, 2017, 50(1): 1151-1156.
[21] ZHANG B, JI D, LIU S, et al. Autonomous underwater vehicle navigation: a review[J]. Ocean Engineering, 2023, 273(7): 113861.
[22] KARIMI H R, LU Y. Guidance and control methodologies for marine vehicles: a survey[J].Control Engineering Practice, 2021, 111(6): 104785.
[23] YAN J, GUO Z, YANG X, et al. Finite-time tracking control of autonomous underwater vehi￾cle without velocity measurements[J]. IEEE Transactions on Systems, Man, and Cybernetics:Systems, 2021, 52(11): 6759-6773.
[24] TIJJANI A S, CHEMORI A, CREUZE V. A survey on tracking control of unmanned underwatervehicles: experiments-based approach[J]. Annual Reviews in Control, 2022, 54(2): 125-147.
[25] LIU J, ZHAO M, QIAO L. Adaptive barrier Lyapunov function-based obstacle avoidance control for an autonomous underwater vehicle with multiple static and moving obstacles[J]. Ocean engineering, 2022, 243(1): 110303.
[26] PINHEIRO P M, NETO A A, GRANDO R B, et al. Trajectory planning for hybrid unmanned aerial underwater vehicles with smooth media transition[J]. Journal of Intelligent & Robotic Systems, 2022, 104(3): 46.
[27] MU X, HE B, WU S, et al. A practical INS/GPS/DVL/PS integrated navigation algorithm and its application on Autonomous Underwater Vehicle[J]. Applied Ocean Research, 2021, 106(1):102441.
[28] CAO X, REN L, SUN C. Research on obstacle detection and avoidance of autonomous underwater vehicle based on forward-looking sonar[J]. IEEE Transactions on Neural Networks and Learning Systems, 2022, 34(11): 9198-9208.
[29] HUANG H, TANG Q, LI J, et al. A review on underwater autonomous environmental perception and target grasp, the challenge of robotic organism capture[J]. Ocean Engineering, 2020, 195(1): 106644.
[30] DINAKARAN R, ZHANG L, LI C T, et al. Robust and fair undersea target detection with automated underwater vehicles for biodiversity data collection[J]. Remote Sensing, 2022, 14(15): 3680.
[31] PERKINS W, BRADY L. CURV III (Cable-Controlled Underwater Recovery Vehicle) characteristics and mission applications.[R]. NOSC/TD-651. NAVAL OCEAN SYSTEMS CENTER SAN DIEGO CA, 1984.
[32] KYO M, HIYAZAKI E, TSUKIOKA S, et al. The sea trial of ‘KAIKO’, the full ocean depth research ROV[C]//Challenges of Our Changing Global Environment. Conference Proceedings.OCEANS’95 MTS/IEEE: Vol. 3. IEEE, 1995: 1991-1996.
[33] KHATIB O, YEH X, BRANTNER G, et al. Ocean one: a robotic avatar for oceanic discovery[J]. IEEE Robotics & Automation Magazine, 2016, 23(4): 20-29.
[34] BRANTNER G. Human-robot collaboration in challenging environments[M]. Stanford Uni￾versity, 2018: 63-78.
[35] YEH X. Development of an underwater humanoid robotic diver[D]. Stanford University, 2017.
[36] WILBY A, LO E. Low-cost, open-source hovering autonomous underwater vehicle (HAUV) for marine robotics research based on the BlueROV2[C]//2020 IEEE/OES Autonomous Under￾water Vehicles Symposium (AUV). IEEE, 2020: 1-5.
[37] 连琏, 马厦飞, 陶军. “海马”号 4500 米级 ROV 系统研发历程[J]. 船舶与海洋工程, 2015,31(1): 9-12.
[38] 任峰, 张莹, 张丽婷, 等. “海龙 Ⅲ”号 ROV 系统深海试验与应用研究[J]. 海洋技术学报,2019, 38(2): 30-35.
[39] 祖祎. 小型水下机器人运动控制系统研究与仿真[D]. 沈阳工业大学, 2022: 34-41.
[40] 孙海超, 邓彦松. 基于矢量控制的开架式水下机器人[J]. 兵工自动化, 2022, 41(10): 75-78.
[41] ZHAO S, YUH J. Experimental study on advanced underwater robot control[J]. IEEE transac￾tions on robotics, 2005, 21(4): 695-703.
[42] DE KRUIF B J, COZIJN H, VAN DER SCHAAF H, et al. Control design for a multi-regime 6-DOF underwater vehicle; development of MARIN’s modular AUV[J]. IFAC-PapersOnLine,2019, 52(21): 230-235.
[43] GAVRILINA E, VELTISHEV V, KROPOTOV A. Attitude control system of a highly maneuverable hybrid ROV for ship-hull inspection[C]//OCEANS 2021: San Diego–Porto. IEEE,2021: 1-6.
[44] BORASE R P, MAGHADE D, SONDKAR S, et al. A review of PID control, tuning methods and applications[J]. International Journal of Dynamics and Control, 2021, 9(2): 818-827.
[45] 王建华, 宋燕, 魏国亮, 等. 串级 PID 控制在水下机器人俯仰控制系统中的应用[J]. 上海理工大学学报, 2017, 39(3): 229-235.
[46] NGUYEN A T, TANIGUCHI T, ECIOLAZA L, et al. Fuzzy control systems: past, present and future[J]. IEEE Computational Intelligence Magazine, 2019, 14(1): 56-68.
[47] 张国良. 模糊控制及其 MATLAB 应用[M]. 西安交通大学出版社, 2002: 61-89.
[48] KHODAYARI M H, BALOCHIAN S. Modeling and control of autonomous underwater vehicle (AUV) in heading and depth attitude via self-adaptive fuzzy PID controller[J]. Journal of Marine Science and Technology, 2015, 20(3): 559-578.
[49] XIE Y, ZHU A, HUANG Z, et al. Research on the control performance of depth-fixed motion of underwater vehicle based on fuzzy-PID[J]. Journal of Robotics, 2023, 2023: 4168433.
[50] PAN X, XU G, HUANG Z, et al. Adaptive fuzzy control design based on nonlinear system of underwater vehicle[C]//Proceedings of the International Offshore and Polar Engineering Con￾ference. Shanghai, China, 2022: 1175 - 1181.
[51] DING H, WANG D. Autonomous underwater vehicle heading control based on sliding mode fuzzy control[C]//Proceedings of the Second International Conference on Modelling and Sim￾ulation. 2009: 505-508.
[52] TANAKITKORN K, WILSON P A, TURNOCK S R, et al. Sliding mode heading control of an overactuated, hover-capable autonomous underwater vehicle with experimental verification[J]. Journal of Field Robotics, 2018, 35(3): 396-415.
[53] HONG E Y, SOON H G, CHITRE M. Depth control of an autonomous underwater vehicle,STARFISH[C]//OCEANS’10 IEEE SYDNEY. IEEE, 2010: 1-6.
[54] SARHADI P, NOEI A R, KHOSRAVI A. Adaptive integral feedback controller for pitch and yaw channels of an AUV with actuator saturations[J]. ISA transactions, 2016, 65(6): 284-295.
[55] GUO S, DU J, LIN X, et al. Adaptive fuzzy sliding mode control for spherical underwater robots[C]//2012 IEEE International Conference on Mechatronics and Automation. IEEE, 2012:1681-1685.
[56] ZHU X, TAN F. Attitude control method of six degree of freedom autonomous underwater vehicle based on RBF neural network[C]//Proceedings of the 7th International Conference on Robotics and Artificial Intelligence. 2021: 70-75.
[57] WU Y, WEI Y, AN D, et al. A hybrid control strategy based on neural network and PID for underwater robot hovering[C]//2023 26th International Conference on Computer Supported Cooperative Work in Design (CSCWD). IEEE, 2023: 1843-1848.
[58] MAKAVITA C D, NGUYEN H D, RANMUTHUGALA D, et al. Composite model reference adaptive control for an unmanned underwater vehicle[J]. Underwater Technology, 2015, 33(2):81-93.
[59] YU W, LIANG Q, XIONG N, et al. MPC-based motion control of underwater vehicle with fixed depth[C]//EEI 2022; 4th International Conference on Electronic Engineering and Informatics.VDE, 2022: 1-4.
[60] 韩京清. 自抗扰控制技术: 估计补偿不确定因素的控制技术[M]. 国防工业出版社, 2008:17-41.
[61] 韩京清. 自抗扰控制器及其应用[J]. 控制与决策, 1998, 13(1): 19-23.
[62] 黄健. 自抗扰技术在水下航行体横滚姿态控制中的应用研究[J]. 船舶工程, 2014, 36(S1):131-134.
[63] 赵兴隆, 商蕾, 乔玉蓬. 基于自抗扰控制的小型 ROV 姿态与深度控制研究[J]. 中国修船,2022, 35(2): 42-46.
[64] FOSSEN T I. Handbook of marine craft hydrodynamics and motion control[M]. John Wiley & Sons, 2011: 69-108.
[65] 张赫, 庞永杰, 李晔. 潜水器水动力系数计算方法研究[J]. 武汉理工大学学报 (交通科学与工程版), 2011, 35(1): 15-18.
[66] 刘和平. 浅水水下机器人设计与控制技术工程研究[D]. 上海大学, 2009: 65-81.