Volume 23 Issue 6
Dec.  2023
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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2023  >  23(6): 314-326
TUO Yu-long, KANG Cai-xia, WANG Sha-sha, DAI Dong-chen, GAO Shuang, LI Li-li. Adjacent cross-coupling synchronous formation control with collision avoidance for multiple ships under unknown disturbances[J]. Journal of Traffic and Transportation Engineering, 2023, 23(6): 314-326. doi: 10.19818/j.cnki.1671-1637.2023.06.021
Citation: TUO Yu-long, KANG Cai-xia, WANG Sha-sha, DAI Dong-chen, GAO Shuang, LI Li-li. Adjacent cross-coupling synchronous formation control with collision avoidance for multiple ships under unknown disturbances[J]. Journal of Traffic and Transportation Engineering, 2023, 23(6): 314-326. doi: 10.19818/j.cnki.1671-1637.2023.06.021
shu

Adjacent cross-coupling synchronous formation control with collision avoidance for multiple ships under unknown disturbances

doi: 10.19818/j.cnki.1671-1637.2023.06.021
  • 1.

    College of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, Liaoning, China

  • 2.

    School of Mechanical and Electrical Engineering, Shaoxing University, Shaoxing 312000, Zhejiang, China

Funds:

National Natural Science Foundation of China 52101298

National Natural Science Foundation of China 52201409

China Postdoctoral Science Foundation 2019M661082

Fundamental Research Funds for the Central Universities 3132022104

Natural Science Foundation of Zhejiang Province LQ22E090007

Dalian Innovative Support Project for High-Level Talents 2023RQ066

More Information
  • Author Bio:

    TUO Yu-long(1990-), male, associate professor, PhD, tuoyulong@dlmu.edu.cn

  • Received Date: 2023-06-17
  • Publish Date: 2023-12-25
    Abstract
  • In view of the poor synchronization performance and obstacle collision risk during formation navigation under unknown marine disturbances, a distributed adjacent cross-coupling synchronous formation robust control method with collision avoidance was proposed for multiple ships, and an adjacent cross-coupling synchronous control strategy was proposed to achieve higher synchronous control accuracy, and the unknown marine disturbances were estimated by the neural network. In order to effectively prevent collision risks between ships and obstacles, as well as between ships, the artificial potential field method was applied to the multi-ship formation control system. The effectiveness of the proposed method was tested by simulating the parallel formation navigation scenarios of five ships facing multiple obstacles and unknown marine disturbances. Research results show that all ships can navigate in the expected formation after safely avoiding the obstacles in considering obstacles and external marine disturbances. After about 9 s, the ships can reach consistent velocities. Although the velocities of the ships fluctuate slightly when there are obstacles, the ships are able to continue navigating with consistent velocity after 30 s. Besides, there also exist small oscillations in the position and velocity tracking errors, position synchronization errors of adjacent ships, and neural network approximation errors. However, these errors can eventually converge to 0 after 30 s, ensuring the synchronization of the position and velocity information of the five ships. Therefore, the proposed method can not only solve the problem of poor synchronization performance when ships are sailing in formation under unknown marine disturbances, but also effectively reduce the collision risk between ships and obstacles, as well as between ships. To some extent, the autonomy and safety of the ships during formation navigation have been improved.

     

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