Volume 22 Issue 4
Aug.  2022
Turn off MathJax
Article Contents
LIU Chen-guang, HE Zhi-bo, CHU Xiu-min, WU Wen-xiang, LI Song-long, XIE Shuo. Overview on ship formation control[J]. Journal of Traffic and Transportation Engineering, 2022, 22(4): 10-27. doi: 10.19818/j.cnki.1671-1637.2022.04.002
Citation: LIU Chen-guang, HE Zhi-bo, CHU Xiu-min, WU Wen-xiang, LI Song-long, XIE Shuo. Overview on ship formation control[J]. Journal of Traffic and Transportation Engineering, 2022, 22(4): 10-27. doi: 10.19818/j.cnki.1671-1637.2022.04.002

Overview on ship formation control

doi: 10.19818/j.cnki.1671-1637.2022.04.002
Funds:

National Natural Science Foundation of China 52001240

Natural Science Foundation of Chongqing cstc2021jcyj-msxmX1220

Open Project Program of Science and Technology on Hydrodynamics Laboratory 6142203210204

Fundamental Research Funds for the Central Universities 213244001

More Information
  • Author Bio:

    LIU Chen-guang(1988-), male, associate professor, PhD, liuchenguang@whut.edu.cn

    CHU Xiu-min(1969-), male, professor, PhD, chuxm@whut.edu.cn

  • Received Date: 2022-01-19
    Available Online: 2022-10-08
  • Publish Date: 2022-08-25
  • The characteristics of ship formation control were studied, and its current situation and methods were analyzed from the aspects of the structure of ship formation control, formation path planning, formation motion modeling, and formation motion control. The principle of ship formation control was introduced, and the mathematical representation methods and application scenarios of leader-follower structure, virtual structure, graph theory structure, and behavior-based structure of ship formations were described. For the path planning of ship formations, the latest methods and characteristics of formation environment modeling, global path planning, and local collision avoidance planning were summarized, and the local collision avoidance effect of ship formations based on the particle swarm optimization algorithm was demonstrated. For the motion modeling of ship formation control, a hydrodynamic model of ship formations considering the disturbance, control delay, and constraints was built and verified in the contral scenario of a ship formation passing through the lock waterway. For the motion control of ship formations, the characteristics of typical centralized, decentralized, and distributed formation controllers were summarized. It was pointed out that the distributed formation controller had better robustness and scalability, and hence, a formation navigation controller based on the distributed model predictive control was designed. Analysis results show that the technical bottleneck of ship formation control is mainly reflected in the aspects such as the integration of manned/unmanned formations, inland ship formation control mainly based on shore-side driving and control, ship formation control under uncertain disturbances, robust ship formation control under communication constraints, ship formation control in special waters, and consistency of ship formation control. In the future development of ship formations, the following key problems should be addressed: distributed collaborative control of ship formations, diversified control of ship formation tasks, ship formation control based on the biological group mechanism, ship formation control in special waters, and application of artificial intelligence technology in ship formation control.

     

  • loading
  • [1]
    REYHANOGLU M. Exponential stabilization of an underactuated autonomous surface vessel[J]. Automatica, 1997, 33(12): 2249-2254. doi: 10.1016/S0005-1098(97)00141-6
    [2]
    YUAN Yu-peng, WANG Kang-yu, YIN Qi-zhi, et al. Review on ship speed optimization[J]. Journal of Traffic and Transportation Engineering, 2020, 20(6): 18-34. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JYGC202006005.htm
    [3]
    ROBERTS G N, ZIRILLI A, TIANO A, et al. A fuzzy controller for integrated ship motion control[J]. IFAC Proceedings Volumes, 1999, 32(2): 8279-8284. doi: 10.1016/S1474-6670(17)57412-1
    [4]
    MCGOOKIN E W, MURRAY-SMITH D J, LI Yun, et al. Ship steering control systemoptimisation using genetic algorithms[J]. Control Engineering Practice, 2000, 8(4): 429-443. doi: 10.1016/S0967-0661(99)00159-8
    [5]
    ZHANG Rong-jun, CHEN Yao-bin, SUN Zeng-qi, et al. Path control of a surface ship in restricted waters using sliding mode[J]. IEEE Transactions on Control Systems Technology, 2000, 8(4): 722-732. doi: 10.1109/87.852916
    [6]
    NIJMEIJER H, PETTERSEN K Y. Underactuated ship tracking control: theory and experiments[J]. International Journal of Control, 2001, 74(14): 1435-1446. doi: 10.1080/00207170110072039
    [7]
    PAUL K C W. Navigation strategies for multiple autonomous mobile robots moving in formation[J]. Journal of Robotic Systems, 1991, 8(2): 177-195. doi: 10.1002/rob.4620080204
    [8]
    ZHOU Xiang-yu, WU Zhao-lin, WANG Feng-wu, et al. Definition of autonomous ship and its autonomy level[J]. Journal of Traffic and Transportation Engineering, 2019, 19(6): 149-162. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JYGC201906016.htm
    [9]
    LIU Chen-guang, CHU Xiu-min, WU Qing, et al. A review and prospect of USV research[J]. Shipbuilding of China, 2014, 55(4): 194-205. (in Chinese) doi: 10.3969/j.issn.1000-4882.2014.04.024
    [10]
    HOU Rui-chao, TANG Zhi-cheng, WANG Bo, et al. Development status and trend of intelligent technology for unmanned surface vehicles[J]. Shipbuilding of China, 2020, 61(S1): 211-220. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZGZC2020S1026.htm
    [11]
    PENG Zhou-hua, WU Wen-tao, WANG Dan, et al. Coordinated control of multiple unmanned surface vehicles: recent advances and future trends[J]. Chinese Journal of Ship Research, 2021, 16(1): 51-64, 82. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JCZG202101006.htm
    [12]
    LEWIS M A, TAN K H. High precision formation control of mobile robots using virtual structures[J]. Autonomous Robots, 1997, 4(4): 387-403. doi: 10.1023/A:1008814708459
    [13]
    BALCH T, ARKIN R C. Behavior-based formation control for multirobot teams[J]. IEEE Transactions on Robotics and Automation, 1998, 14(6): 926-939. doi: 10.1109/70.736776
    [14]
    BEARD R W, LAWTON J, HADAEGH F Y. A coordination architecture for spacecraft formation control[J]. IEEE Transactions on Control Systems Technology, 2001, 9(6): 777-790. doi: 10.1109/87.960341
    [15]
    DAS A K, FIERRO R, KUMAR V, et al. A vision-based formation control framework[J]. IEEE Transactions on Robotics and Automation, 2002, 18(5): 813-825. doi: 10.1109/TRA.2002.803463
    [16]
    SKJETNE R, MOI S, FOSSEN T I. Nonlinear formation control of marine craft[C]//IEEE. Proceedings of the 41st IEEE Conference on Decision and Control. New York: IEEE, 2002: 1699-1704.
    [17]
    ZHANG Wei, WANG Nai-xin, WEI Shi-lin, et al. Overview of unmanned underwater vehicle swarm development status and key technologies[J]. Journal of Harbin Engineering University, 2020, 41(2): 289-297. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-HEBG202002020.htm
    [18]
    XING Zhi-wei, LI Si, LUO Qian. Formation control model of airport pavement deicing vehicles[J]. Journal of Traffic and Transportation Engineering, 2019, 19(4): 182-190. (in Chinese) doi: 10.3969/j.issn.1671-1637.2019.04.017
    [19]
    LIU Chen-guang, CHU Xiu-min, OUYANG Xue, et al. Simulation platform for course keeping control of underactuated surface model ships[J]. Navigation of China, 2016, 39(4): 1-5, 112. (in Chinese) doi: 10.3969/j.issn.1000-4653.2016.04.001
    [20]
    YAN Xin-ping, WU Chao, MA Feng. Conceptual design of navigation brain system for intelligent cargo ship[J]. Navigation of China, 2017, 40(4): 95-98, 136. (in Chinese) doi: 10.3969/j.issn.1000-4653.2017.04.020
    [21]
    IHLE IA F, ARCAK M, FOSSEN T I. Passivity-based designs for synchronized path-following[J]. Automatica, 2007, 43(9): 1508-1518. doi: 10.1016/j.automatica.2007.02.018
    [22]
    FAHIMI F. Sliding-mode formation control for underactuated surface vessels[J]. IEEE Transactions on Robotics, 2007, 23(3): 617-622. doi: 10.1109/TRO.2007.898961
    [23]
    PENG Zhou-hua, WANG Jun, WANG Dan, et al. An overview of recent advances in coordinated control of multiple autonomous surface vehicles[J]. IEEE Transactions on Industrial Informatics, 2020, 17(2): 732-745.
    [24]
    KE Tao, ZHANG Heng, SONG Jia. Research on the technology of anti-jamming of the same frequency for the formation of USV[J]. Shipbuilding of China, 2020, 61(S1): 105-112. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZGZC2020S1013.htm
    [25]
    ZHANG Wei-dong, LIU Xiao-cheng, HAN Peng. Progress and challenges of overwater unmanned systems[J]. Acta Automatica Sinica, 2020, 46(5): 847-857. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-MOTO202005002.htm
    [26]
    SUN Zhi-jian, ZHANG Guo-qing, LU Yu, et al. Leader- follower formation control of underactuated surface vehicles based on sliding mode control and parameter estimation[J]. ISA Transactions, 2018, 72: 15-24. doi: 10.1016/j.isatra.2017.11.008
    [27]
    ENCARN ACAO P, PASCOAL A. Combined trajectory tracking and path following: an application to the coordinated control of autonomous marine craft[C]//IEEE. Proceedings of the 40th IEEE Conference on Decision and Control. New York: IEEE, 2001: 964-969.
    [28]
    PEREIRA G A S, PEREIRA G A S, DAS A K, et al. Formation control with configuration space constraints[C]//IEEE. Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems. New York: IEEE, 2003: 2755-2760.
    [29]
    LI Yun, XIAO Ying-jie. Combination of leader-follower method and potential function about ship formation control[J]. Control Theory and Applications, 2016, 33(9): 1259-1264. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-KZLY201609016.htm
    [30]
    SHI Hong, WANG Long, CHU Tian-guang. Virtual leader approach to coordinated control of multiple mobile agents with asymmetric interactions[J]. Physica D: Nonlinear Phenomena, 2006, 213(1): 51-65. doi: 10.1016/j.physd.2005.10.012
    [31]
    WANG Dong-mei, FANG Hua-jing. Virtual leaders-based control of flocking motion of intelligent swarm[J]. Journal of Huazhong University of Science and Technology (Natural Science Edition), 2008, 36(10): 5-7. (in Chinese) doi: 10.3321/j.issn:1671-4512.2008.10.002
    [32]
    WANG Bin. Research on robust adaptive formation control of multiple dynamic positioning vessels[D]. Harbin: Harbin Engineering University, 2017. (in Chinese)
    [33]
    PENG Zhou-hua, WANG Dan, YAO Yu-bin, et al. Robust adaptive formation control with autonomous surface vehicles[C]// IEEE. Proceedings of the 29th Chinese Control Conference. New York: IEEE, 2010: 2115-2120.
    [34]
    DUNBAR W B, CAVENEY D S. Distributed receding horizon control of vehicle platoons: stability and string stability[J]. IEEE Transactions on Automatic Control, 2011, 57(3): 620-633.
    [35]
    ÖGREN P, EGERSTEDT M, HU X. A control Lyapunov function approach to multiagent coordination[J]. IEEE Transactions on Robotics and Automation, 2001, 18(5): 847-851.
    [36]
    GHOMMEM J, MNIF F, POISSON G, et al. Nonlinear formation control of a group of underactuated ships[C]// IEEE. Proceedings of the IEEE OCEANS 2007-Europe. New York: IEEE, 2007: 1-8.
    [37]
    QIN Zi-he, LIN Zhuang, LI Ping, et al. Formation control of underactuated ships with input saturation[J]. Journal of Huazhong University of Science and Technology (Natural Science Edition), 2015, 43(8): 75-78. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-HZLG201508016.htm
    [38]
    REN W, BEARD R. Decentralized scheme for spacecraft formation flying via the virtual structure approach[J]. Journal of Guidance, Control, and Dynamics, 2004, 27(1): 73-82. doi: 10.2514/1.9287
    [39]
    MEHRJERDI H, GHOMMAM J, SAAD M. Nonlinear coordination control for a group of mobile robots using a virtual structure[J]. Mechatronics, 2011, 21(7): 1147-1155. doi: 10.1016/j.mechatronics.2011.06.006
    [40]
    CUI Rong-xin, XU De-min, SHEN Meng, et al. Formation control of robots based on behavior[J]. Computer Simulation, 2006, 23(2): 137-139. (in Chinese) doi: 10.3969/j.issn.1006-9348.2006.02.040
    [41]
    BALCH T, ARKIN R C. Behavior-based formation control for multirobot teams[J]. IEEE Transactions on Robotics and Automation, 1998, 14(6): 926-939. doi: 10.1109/70.736776
    [42]
    PANG Shi-kun, LI Ying-hui, YI Hong. Joint formation control with obstacle avoidance of towfish and multiple autonomous underwater vehicles based on graph theory and the null-space-based method[J]. Sensors, 2019, 19(11): 2591. doi: 10.3390/s19112591
    [43]
    ANTONELLI G, ARRICHIELLO F, CHIAVERINI S. Experiments of formation control with collisions avoidance using the null-space-based behavioral control[C]//IEEE. 2006 14th Mediterranean Conference on Control and Automation. New York: IEEE, 2006: 1-6.
    [44]
    ROSALES C D, SARCINELLI-FILHO M, SCAGLIA G, et al. Formation control of unmanned aerial vehicles based on the null-space[C]//IEEE. 2014 International Conference on Unmanned Aircraft Systems (ICUAS). New York: IEEE, 2014: 229-236.
    [45]
    AHMAD S, FENG Zhi, HU Guo-qiang. Multi-robot formation control using distributed null space behavioral approach[C]//IEEE. International Conference on Robotics and Automation. New York: IEEE, 2014: 3607-3612.
    [46]
    SEOK P B, JIN Y S. An error transformation approach for connectivity-preserving and collision-avoiding formation tracking of networked uncertain underactuated surface vessels[J]. IEEE Transactions on Cybernetics, 2018, DOI: 10.1109/TCYB.2018.2834919.
    [47]
    QIN Qi. Formation control for marine surface vessels based on rigid structure[D]. Dalian: Dalian Maritime University, 2018. (in Chinese)
    [48]
    HUANG Chen-feng, ZHANG Xian-ku, ZHANG Guo-qing. Improved decentralized finite-time formation control of underactuated USVs via a novel disturbance observer[J]. Ocean Engineering, 2019, 174: 117-124. doi: 10.1016/j.oceaneng.2019.01.043
    [49]
    QU Cheng-gang, CAO Xi-bin, ZHANG Ze-xu. Multi-agent system formation integrating virtual leaders into artificial potentials[J]. Journal of Harbin Institute of Technology, 2014, 46(5): 1-5. (in Chinese) doi: 10.3969/j.issn.1009-1971.2014.05.001
    [50]
    WANG Shu-feng, ZHANG Jun-xin, ZHANG Jun-you. Intelligent vehicles formation control based on artificial potential field and virtual leader[J]. Journal of Shanghai Jiao Tong University, 2020, 54(3): 305-311. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-SHJT202003011.htm
    [51]
    WANG Nan, XU Jie-qiong. Graph theory and behavior based networked formation control for spacecraft in deep space[J]. Journal of Shenyang University of Technology, 2011, 33(4): 439-444. (in Chinese)
    [52]
    LIU Chen-guang, QI Jun-lin, CHU Xiu-min, et al. Cooperative ship formation system and control methods in the ship lock waterway[J]. Ocean Engineering, 2021, 226: 108826. doi: 10.1016/j.oceaneng.2021.108826
    [53]
    OUYANG Zi-lu, WANG Hong-dong, HUANG Yi, et al. Path planning technologies for USV formation based on improved RRT[J]. Chinese Journal of Ship Research, 2020, 15(3): 18-24. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JCZG202003003.htm
    [54]
    BARRAQUAND J, LATOMBE J C. Robot motion planning: a distributed representation approach[J]. The International Journal of Robotics Research, 1991, 10(6): 628-649. doi: 10.1177/027836499101000604
    [55]
    HUANG Zhen-kui, SHEN Wen-zhu, DU Qiao-ling, et al. Studies on control system of small-scale float-garbage automatic cruise ship based on open-water traversal algorithm[J]. Journal of Jilin University (Information Science Edition), 2019, 37(2): 208-215. (in Chinese) doi: 10.3969/j.issn.1671-5896.2019.02.015
    [56]
    HART P E, NILSSON N J, RAPHAEL B. A formal basis for the heuristic determination of minimum cost paths[J]. IEEE Transactions on Systems Science and Cybernetics, 1968, 4(2): 100-107. doi: 10.1109/TSSC.1968.300136
    [57]
    SETHIANJ A. A fast marching level set method for monotonically advancing fronts[J]. Proceedings of the National Academy of Sciences, 1996, 93(4): 1591-1595. doi: 10.1073/pnas.93.4.1591
    [58]
    CHIANG H T L, TAPIA L. COLREG-RRT: an RRT- based COLREGS-compliant motion planner for surface vehicle navigation[J]. IEEE Robotics and Automation Letters, 2018, 3(3): 2024-2031. doi: 10.1109/LRA.2018.2801881
    [59]
    XIN Jun-feng, ZHONG Jia-bao, YANG Feng-ru, et al. An improved genetic algorithm for path-planning of unmanned surface vehicle[J]. Sensors, 2019, 19(11): 2640. doi: 10.3390/s19112640
    [60]
    KIRKPATRICK S, GELATT C D, VECCHI M P. Optimization by simulated annealing[J]. Science, 1983, 220(4598): 671-680. doi: 10.1126/science.220.4598.671
    [61]
    LYRIDIS D V. An improved ant colony optimization algorithm for unmanned surface vehicle local path planning with multi-modality constraints[J]. Ocean Engineering, 2021, 241: 109890. doi: 10.1016/j.oceaneng.2021.109890
    [62]
    EBERHART R, KENNEDY J. A new optimizer using particle swarm theory[C]//IEEE. Proceedings of the Sixth International Symposium on Micro Machine and Human Science. New York: IEEE, 1995: 39-43.
    [63]
    WANG Le, LI Shi-jie, LIU Jia-lun, et al. Ship docking and undocking control with adaptive-mutation beetle swarm prediction algorithm[J]. Ocean Engineering, 2022, 251: 111021.
    [64]
    SHI En-xiu, CHEN Min-min, LI Jun, et al. Research on method of global path-planning for mobile robot based on ant-colony algorithm[J]. Transactions of the Chinese Society of Agricultural Machinery, 2014, 45(6): 53-57. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-NYJX201406009.htm
    [65]
    LIU Yuan-chang, BUCKNALL R. Path planning algorithm for unmanned surface vehicle formations in a practical maritime environment[J]. Ocean Engineering, 2015, 97: 126-144.
    [66]
    MA Yong, HU Meng-qi, YAN Xin-ping. Multi-objective path planning for unmanned surface vehicle with currents effects[J]. ISA Transactions, 2018, 75: 137-156.
    [67]
    SANG Hong-qiang, YOU Yu-song, SUN Xiu-jun, et al. The hybrid path planning algorithm based on improved A* and artificial potential field for unmanned surface vehicle formations[J]. Ocean Engineering, 2021, 223: 108709.
    [68]
    GU Chen. Application of improved A* algorithm in robot path planning[J]. Electronic Design Engineering, 2014, 22(19): 96-98, 102. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-GWDZ201419031.htm
    [69]
    CHEN Ruo-nan, WEN Cong-cong, PENG Ling, et al. Application of improved A* algorithm in indoor path planning for mobile robot[J]. Journal of Computer Applications, 2019, 39(4): 1006-1011. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JSJY201904013.htm
    [70]
    SINGH Y, SHARMA S, SUTTON R, et al. A constrained A* approach towards optimal path planning for an unmanned surface vehicle in a maritime environment containing dynamic obstacles and ocean currents[J]. Ocean Engineering, 2018, 168: 187-201.
    [71]
    LIU Chen-guang, MAO Qing-zhou, CHU Xiu-min, et al. An improved A-star algorithm considering water current, traffic separation and berthing for vessel path planning[J]. Applied Sciences, 2019, 9(6): 1057.
    [72]
    NAEEM W, IRWIN G W, YANG A. COLREGs-based collision avoidance strategies for unmanned surface vehicles[J]. Mechatronics, 2012, 22(6): 669-678.
    [73]
    LYU Hong-guang, YIN Yong. Path planning of autonomous ship based on electronic chart vector data modeling[J]. Journal of Transportation Information and Safety, 2019, 37(5): 94-106. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JTJS201905013.htm
    [74]
    LYU Hong-guang, YIN Yong. COLREGS-constrained real-time path planning for autonomous ships using modified artificial potential fields[J]. The Journal of Navigation, 2019, 72(3): 588-608.
    [75]
    YOO B, KIM J. Path optimization for marine vehicles in ocean currents using reinforcement learning[J]. Journal of Marine Science and Technology, 2016, 21(2): 334-343.
    [76]
    XIE Shuo. Beetle antenna search based ship motion modeling and collision avoidance methods[D]. Wuhan: Wuhan University of Technology, 2020. (in Chinese)
    [77]
    LEE S M, KWON K Y, JOONGSEON J. A fuzzy logic for autonomous navigation of marine vehicles satisfying COLREG guidelines[J]. International Journal of Control, Automation, and Systems, 2004, 2(2): 171-181.
    [78]
    DAI Shi-lu, HE Shu-de, LIN Hai, et al. Platoon formation control with prescribed performance guarantees for USVs[J]. IEEE Transactions on Industrial Electronics, 2017, 65(5): 4237-4246.
    [79]
    LIN An-hui, JIANG De-song, ZENG Jian-ping. Underactuated ship formation control with input saturation[J]. Acta Automatica Sinica, 2018, 44(8): 1496-1504. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-MOTO201808013.htm
    [80]
    ZHOU Wei-dong, LIU Yi-meng, ZHA Yang-yang. Anti-time- delay unmanned surface vehicle formation control and transformation[J]. Journal of Harbin Engineering University, 2019, 40(11): 1865-1869. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-HEBG201911010.htm
    [81]
    CAI Xing, XIE Lei, SU Hong-ye, et al. Distributed model predictive control based on cascade processes[J]. Acta Automatica Sinica, 2013, 39(5): 44-52. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-MOTO201305007.htm
    [82]
    SCATTOLINI R. Architectures for distributed and hierarchical model predictive control—a review[J]. Journal of Process Control, 2009, 19(5): 723-731.
    [83]
    XIAO Ya-hui, WANG Xin-min, WANG Xiao-yan, et al. An effective controller design of formation flight of unmanned aerial vehicles (UAV)[J]. Journal of Northwestern Polytechnical University, 2011, 29(6): 834-838. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XBGD201106003.htm
    [84]
    LI Tie-shan, ZHAO Rong, CHEN C L P, et al. Finite-time formation control of under-actuated ships using nonlinear sliding mode control[J]. IEEE Transactions on Cybernetics, 2018, 48(11): 3243-3253.
    [85]
    DO K D. Practical formation control of multiple underactuated ships with limited sensing ranges[J]. Robotics and Autonomous Systems, 2011, 59(6): 457-471.
    [86]
    SHOJAEI K. Leader-follower formation control of underactuated autonomous marine surface vehicles with limited torque[J]. Ocean Engineering, 2015, 105: 196-205.
    [87]
    DENG Yun. Research on adaptive control of ship formation collision avoidance[J]. Ship Science and Technology, 2017, 39(20): 31-33. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JCKX201720012.htm
    [88]
    MAHMOOD A, KIM Y. Decentrailized formation flight control of quadcopters using robust feedback linearization[J]. Journal of the Franklin Institute, 2017, 354(2): 852-871.
    [89]
    HUANG Chen-feng, ZHANG Xian-ku, ZHANG Guo-qing. Adaptive neural finite-time formation control for multiple underactuated vessels with actuator faults[J]. Ocean Engineering, 2021, 222: 108556.
    [90]
    ZHANG Hao. Research on the distributed formation control and optimization of multi-agent system[D]. Xi'an: Xidian University, 2019. (in Chinese)
    [91]
    NEGENBORN R R, MAESTRE J M. Distributed model predictive control: an overview and roadmap of future research opportunities[J]. IEEE Control Systems Magazine, 2014, 34(4): 87-97.
    [92]
    GAO Yu-long, XIA Yuan-qing, DAI Li. Cooperative distributed model predictive control of multiple coupled linear systems[J]. IET Control Theory and Applications, 2015, 9(17): 2561-2567.
    [93]
    FERRAMOSCA A, LIMON D, ALVARADO I, et al. Cooperative distributed MPC for tracking[J]. Automatica, 2013, 49(4): 906-914.
    [94]
    LIU Teng-fei, JIANG Zhong-ping. Distributed formation control of nonholonomic mobile robots without global position measurements[J]. Automatica, 2013, 49(2): 592-600.
    [95]
    ZHOU Zhen, WANG Hong-bin, WANG Yue-ling, et al. Distributed formation control for multiple quadrotor UAVs under Markovian switching topologies with partially unknown transition rates[J]. Journal of the Franklin Institute, 2019, 356(11): 5706-5728.
    [96]
    ZHENG Hua-rong, WU Jun, WU Wei-min, et al. Cooperative distributed predictive control for collision-free vehicle platoons[J]. IET Intelligent Transport Systems, 2018, 13(5): 816-824.
    [97]
    CHEN Lin-ying, HOPMAN H, NEGENBORN R R. Distributed model predictive control for vessel train formations of cooperative multi-vessel systems[J]. Transportation Research Part C: Emerging Technologies, 2018, 92: 101-118.
    [98]
    CHEN Lin-ying, HOPMAN H, NEGENBORN R R. Distributed model predictive control for cooperative floating object transport with multi-vessel systems[J]. Ocean Engineering, 2019, DOI: 10.1016/j.oceaneng.2019.106515.
    [99]
    ZHENG Hua-rong, NEGENBORN R R, LODEWIJKS G. Cooperative distributed collision avoidance based on ADMM for waterborne AGVs[C]//Springer. Proceedings of 2015 International Conference on Computational Logistics. Berlin: Springer, 2015: 181-194.
    [100]
    China Classification Society. Guidelines of autonomous cargo ships[R]. Beiing: China Classification Society, 2018. (in Chinese)
    [101]
    XU Li-wei. Formation control and stability analysis of connected and automated vehicle platoon[D]. Nanjing: Southeast University, 2019. (in Chinese)
    [102]
    WANG Xiang-ke, LI Xun, ZHENG Zhi-qiang. Survey of developments on multi-agent formation control related problems[J]. Control and Decision, 2013(11): 1601-1613. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-KZYC201311001.htm
    [103]
    TIAN Da-xin, KANG Lu. Research on algorithm of unmanned vehicle formation based on fish school[J]. Unmanned Systems Technology, 2018, 1(4): 62-67. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-UMST201804007.htm
    [104]
    ZHOU Zi-wei, DUAN Hai-bin, FAN Yan-ming. Unmanned aerial vehicle close formation control based on the behavior mechanism in wild geese[J]. Scientia Sinica Technologica, 2017, 47(3): 230-238. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JEXK201703002.htm
    [105]
    YANG Zhi-yuan, DUAN Hai-bin, FAN Yan-ming. Unmanned aerial vehicle formation controller design via the behavior mechanism in wild geese based on Levy flight pigeon-inspired optimization[J]. Scientia Sinica Technologica, 2018, 48(2): 161-169. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JEXK201802005.htm
    [106]
    ZHANG Chi, ZHANG Di, MENG Shang, et al. Trends and prospects of polar navigation research from 24th POAC International Conference[J]. Journal of Transportation Information and Safety, 2017, 35(5): 1-10. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JTJS201705001.htm

Catalog

    Article Metrics

    Article views (2438) PDF downloads(316) Cited by()
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return