Intelligent towing and pushing system for unmanned tugboats under wind and wave disturbances

References

• Abdelghafor Z, Taimuri G, Kujala P, Wang Y, Hirdaris S. 2023. Numerical studies on tugboat performance during pushing operations. Mater Sci Eng. 1288:012003.
   Google Scholar
• Bai W, Zhang W, Cao L, Liu Q. 2023. Adaptive control for multi-agent systems with actuator fault via reinforcement learning and its application on multi-unmanned surface vehicle. Ocean Eng. 280:114545. doi: 10.1016/j.oceaneng.2023.114545.
   Web of Science ®Google Scholar
• Bai Y. 2019. Modeling and simulating of self-propulsion and pushing motion of the tugboat in swell [master's thesis]. Dalian: Daliann Maritime University.
   Google Scholar
• Borkowski P. 2018. Numerical modeling of wave disturbances in the process of ship movement control. Algorithms. 11(9):130. doi: 10.3390/a11090130.
   Google Scholar
• Bruzzone G, Bibuli M, Zereik E, Ranieri A, Caccia M. 2017. Cooperative adaptive guidance and control paradigm for marine robots in an emergency ship towing scenario. Int J Adapt Control Signal Process. 31(4):562–580. doi: 10.1002/acs.v31.4.
   Web of Science ®Google Scholar
• Byrd RH, Gilbert JC, Nocedal J. 2020. A trust region method based on interior point techniques for nonlinear programming. Math Program. 89:149–185. doi: 10.1007/PL00011391.
   Google Scholar
• Chen L, Haseltalab A, Garofano V, Negenborn RR. 2019. Eco-VTF: fuel-efficient vessel train formations for all-electric autonomous ships. Proceedings of the 18th European Control Conference. p. 2543–2550.
   Google Scholar
• Choi JK. 2023. Path-following control of a ship by pushing using a single autonomous tugboat. J Mar Sci Technol. 28:649–657. doi: 10.1007/s00773-023-00946-5.
   Web of Science ®Google Scholar
• De Silva GS, Pinheiro SC. 2021. A new dynamic model of towing cables. Ocean Eng. 220:107653. doi: 10.1016/j.oceaneng.2020.107653.
   Web of Science ®Google Scholar
• Du B, Lu Y, Cheng X, Zhang W, Zou X. 2021. The object-oriented dynamic task assignment for unmanned surface vessels. Eng Appl Artif Intell. 106:104476. doi: 10.1016/j.engappai.2021.104476.
   Web of Science ®Google Scholar
• Du B, Xie W, Li Y, Yang Q, Zhang W, Negenborn RR, Pang Y, Chen H. 2023a. Safe adaptive policy transfer reinforcement learning for distributed multiagent control. IEEE Trans Neural Netw Learn Syst Early Access. doi: 10.1109/TNNLS.2023.3326867.
   Google Scholar
• Du B, Xie W, Zhang W, Chen H. 2023b. A target tracking guidance for unmanned surface vehicles in the presence of obstacles. IEEE Trans Intell Transp Syst Early Access. doi: 10.1109/TITS.2023.3326864.
   Google Scholar
• Du Z, Negenborn RR, Reppa V. 2022. Multi-objective cooperative control for a ship-towing system in congested water traffic environments. IEEE Trans Intell Transp Syst. 23(12):24318–24329. doi: 10.1109/TITS.2022.3208328.
   Web of Science ®Google Scholar
• Fossen TI. 2011. Handbook of marine craft hydrodynamics and motion control. Hoboken, NJ: Wiley.
   Google Scholar
• Gao Q, Song L, Yao J. 2021. Rans prediction of wave-induced ship motions, and steady wave forces and moments in regular waves. J Mar Sci Eng. 9(12):1459. doi: 10.3390/jmse9121459.
   Web of Science ®Google Scholar
• Hajieghrary H, Kularatne D, Hsieh MA. 2018. Differential geometric approach to trajectory planning: cooperative transport by a team of autonomous marine vehicles. Proceedings of Annual American Control Conference. p. 858–863.
   Google Scholar
• He X, Ge H, Sun L, Li Q, Hou Y. 2023. BRGR: multi-agent cooperative reinforcement learning with bidirectional real-time gain representation. Appl Intell. 53:19044–19059. doi: 10.1007/s10489-022-04426-y.
   Web of Science ®Google Scholar
• Hensen H. 2023. Tug use in port: a practical guide. London: Nautical Institute.
   Google Scholar
• Ianagui AS, Tannuri EA. 2019. Automatic load maneuvering and hold-back with multiple coordinated DP vessels. Ocean Eng. 178:357–374. doi: 10.1016/j.oceaneng.2019.02.003
   Web of Science ®Google Scholar
• Ismail MM, Chalhoub NG, Pilipchuk V. 2021. Dynamics and control of a two-ship ensemble connected by a massless towline. Ocean Eng. 234:109295. doi: 10.1016/j.oceaneng.2021.109295.
   Web of Science ®Google Scholar
• Jiang L, Wei R, Wang D. 2023. UAVs rounding up inspired by communication multi-agent depth deterministic policy gradient. Appl Intell. 53(10):11474–11489. doi: 10.1007/s10489-022-03986-3.
   Web of Science ®Google Scholar
• Kumar BA, Selvaraj R, Desingu K, Chelliah TR, Upadhyayula RS. 2020. A coordinated control strategy for a diesel-electric tugboat system for improved fuel economy. IEEE Trans Ind Appl. 56(5):5439–5451. doi: 10.1109/TIA.28.
   Web of Science ®Google Scholar
• Lee DH, Chakir S, Kim YB, Tran DQ. 2020. Control system design for vessel towing system by activating rudders of the towed vessel. Int J Nav Archit Ocean Eng. 12:943–956. doi: 10.1016/j.ijnaoe.2020.11.008.
   Web of Science ®Google Scholar
• Lee SM, Lee JH, Roh MI, Kim KS, Ham SH, Lee HW. 2021. An optimization model of tugboat operation for conveying a large surface vessel. J Comput Des Eng. 8:654–675.
   Web of Science ®Google Scholar
• Liang H, Fu Y, Gao J. 2021. Bio-inspired self-organized cooperative control consensus for crowded UUV swarm based on adaptive dynamic interaction topology. Appl Intell. 51:4664–4681. doi: 10.1007/s10489-020-02104-5.
   Web of Science ®Google Scholar
• Mateos LA. 2020. Bio-inspired adaptive latching system for towing and guiding power-less floating platforms with autonomous robotic boats. arXiv preprint:2001.04293.
   Google Scholar
• Pourbabak H, Chen T, Su W. 2019. In: The energy internet. Amsterdam, The Netherlands: Elsevier; p. 3–19.
   Google Scholar
• Pourbabak H, Chen T, Su W. 2020. Optimization of tugboat propulsion system configurations: a holistic life cycle assessment case study. J Clean Prod. 259:120903. doi: 10.1016/j.jclepro.2020.120903.
   Web of Science ®Google Scholar
• Qin C, Zhang Z, Shang Z, Zhang J, Zhang D. 2023. Adaptive optimal safety tracking control for multiplayer mixed zero-sum games of continuous-time systems. Appl Intell. 53:17460–17475. doi: 10.1007/s10489-022-04348-9.
   Web of Science ®Google Scholar
• Quan TD, Suh JH, Kim YB. 2019. Leader-following control system design for a towed vessel by tugboat. J Ocean Eng Technol. 33(5):462–469. doi: 10.26748/KSOE.2019.075.
   Google Scholar
• Rawlings JB, Mayne DQ, Diehl M. 2017. Model predictive control: theory, computation, and design. 2(10). Madison, WI: Nob Hill Publishing.
   Google Scholar
• Skjetne R, Smogeli O, Fossen TI. 2004. Modeling, identification, and adaptive maneuvering of Cybership II: a complete design with experiments. IFAC Proc Vol. 37(10):203–208. doi: 10.1016/S1474-6670(17)31732-9.
   Google Scholar
• Tao J, Du L, Dehmer M, Wen Y, Xie G, Zhou Q. 2019. Path following control for towing system of cylindrical drilling platform in presence of disturbances and uncertainties. ISA Trans. 95:185–193. doi: 10.1016/j.isatra.2019.04.030.
   PubMed Web of Science ®Google Scholar
• Waltz RA, Morales JL, Nocedal J, Orban D. 2006. An interior algorithm for nonlinear optimization that combines line search and trust region steps. Math Program. 107(3):391–408. doi: 10.1007/s10107-004-0560-5.
   Web of Science ®Google Scholar
• Wu G, Zhao X, Sun Y, Wang L. 2021. Cooperative maneuvering mathematical modeling for multi-tugs towing a ship in the port environment. J Mar Sci Eng. 9(4):384. doi: 10.3390/jmse9040384.
   Web of Science ®Google Scholar
• Xia G, Sun C, Zhao B, Sun X, Xia X. 2022. Robust cooperative trajectory tracking control for an unactuated floating object with multiple vessels system. ISA Trans. 123:263–271. doi: 10.1016/j.isatra.2021.05.043.
   PubMed Web of Science ®Google Scholar
• Zhang Y. 2018. Research on the towing safety of inland towing systems [master's thesis]. Shanghai: Shanghai Jiaotong University.
   Google Scholar
• Zhang Y, Wu W, Chen W, Lu H, Zhang W. 2024. Output-feedback consensus maneuvering of uncertain MIMO strict-feedback multiagent systems based on a high-order neural observer. IEEE Trans Cybern Early Access. doi: 10.1109/TCYB.2024.3351476.
   Google Scholar
• Zheng Y, Tao J, Sun Q, Sun H, Sun M, Chen Z. 2021. An intelligent course keeping active disturbance rejection controller based on double deep Q-network for towing system of unpowered cylindrical drilling platform. Int J Robust Nonlinear Control. 31(17):8463–8480. doi: 10.1002/rnc.v31.17.
   Web of Science ®Google Scholar