Skip to main content

Advertisement

SpringerLink
Log in

ANFIS-based course-keeping control for ships using nonlinear feedback technique

  • Technical Note
  • Published:
Journal of Marine Science and Technology Aims and scope Submit manuscript

Abstract

Course keeping for ships is the core of automatic navigation in marine technology. A nonlinear Nomoto model and a maneuvering model group (MMG) model of Yupeng ship are established and verified by the turning trial at sea, then an adaptive neuro-fuzzy inference system (ANFIS) controller is trained by learning the actual ship trial data. There is a limit to the achievable performance of ANFIS controller as the structure is fixed in the training process, many researchers pursue advanced control strategies to improve performance. In this research, the performance is improved in another way, it modulates control error using proposed nonlinear feedback scheme. The simulation result shows that the settling time of nonlinear controllers decreases considerably, dropping by 62.5% of arc tangent function, dropping by 29.2% of bipolar sigmoid function and dropping by 37.5% of sine function based on nonlinear Nomoto model, and the settling time of nonlinear sine controller decreases by 13.3% based on MMG model. It is a useful research that the control performance is improved by nonlinear feedback technique for project application in marine practice.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

References

  1. KARABOGA D, KAYA E (2017) Training ANFIS by using the artificial bee colony algorithm. Turk J Electr Eng Comput Sci 25(3):1669–1679

    Article  Google Scholar 

  2. Selçuk E (2013) Trajectory optimization of a walking mechanism having revolute joints with clearance using ANFIS approach. Nonlinear Dyn 71(2):75–91

    MathSciNet  Google Scholar 

  3. Thomas B, Sebastian H, Knut G (2013) Nonlinear model predictive control of a magnetic levitation system. Control Eng Pract 21(9):1250–1258

    Article  Google Scholar 

  4. Chen X, Zhang X (2015) Nonlinear feedback control based on ANFIS. 2015 12th international conference on fuzzy systems and knowledge discovery (FSKD), pp 559–563

  5. Yasukawa H, Hirono T, Nakayama Y, Koh KK (2012) Course stability and yaw motion of a ship in steady wind. J Mar Sci Technol 17(3):291–304

    Article  Google Scholar 

  6. Du J, Guo C, Yu S, Zhao Y (2007) Adaptive autopilot design of time varying uncertain ships with completely unknown control coefficient. IEEE J Ocean Eng 32(2):346–352

    Article  Google Scholar 

  7. Johansen TA, Fossen TI (2013) Control allocation a survey. Automatica 49(5):1087–1103

    Article  MathSciNet  Google Scholar 

  8. Zhang X, Zhang G (2015) Design of ship course-keeping autopilot using a sine function based nonlinear feedback technique. J Navig 69(2):246–256

    Article  Google Scholar 

  9. Aarsaether KG, Moan T (2010) Adding the human element to ship manoeuvring simulations. J Navig 63:695–716

    Article  Google Scholar 

  10. Zhang W (2011) Quantitative process control theory. CRC Press, Baco Raton

    Book  Google Scholar 

  11. Lin D, Wang X, Yao Y (2012) Fuzzy neural adaptive tracking control of unknown chaotic systems with input saturation. Nonlinear Dyn 67(4):2889–2897

    Article  MathSciNet  Google Scholar 

  12. Zhang Z, Zhang X, Zhang G (2017) Nonlinear response mathematical model of YUPENG ship. The 36th Chinese control conference, pp 4688–4691

  13. JIA X, ZHANG X (2015) Equivalent rudder angle to wind force and its application. Shipbuild China 56(3):117–123

    Google Scholar 

  14. Nomoto K, Taguchi T, Honda K, Hirano S (1957) On the steering qualities of ships. Int Shipbuild Prog 4(35):354–370

    Article  Google Scholar 

  15. Fossen TI (2011) Handbook of marine craft hydrodynamics and motion control. Wiley, New York

    Book  Google Scholar 

  16. Zhang G, Zhang X (2014) Concise robust adaptive path-following control of underactuated ships using DSC and MLP. IEEE J Ocean Eng 39(4):685–694

    Article  MathSciNet  Google Scholar 

  17. Lei ZL, Guo C (2015) Disturbance rejection control solution for ship steering system with uncertain time delay. Ocean Eng 95(1):78–83

    Article  MathSciNet  Google Scholar 

  18. Chen Y, Zhang R, Zhao X, Gao J (2016) Tracking control of underwater vehicle subject to uncertainties using fuzzy inverse desired trajectory compensation technique. J Mar Sci Technol 21(4):624–650

    Article  Google Scholar 

Download references

Acknowledgements

Much appreciations to each reviewer for their valuable comments and suggestions to improve the quality of this note. This work is partially supported by the National Science Foundation of China (Grant nos. 51679024 and 51779029), the Fundamental Research Funds for the Central University (Grand no. 3132016315), the National High Technology Research and Development Program of China (Grand no. 2015AA016404), and the University 111 Project of China (Grand no. B08046).

Author information

Authors and Affiliations

  1. Navigation College, Dalian Maritime University, Dalian, Liaoning, China

    Zhiheng Zhang, Xianku Zhang & Guoqing Zhang

Authors
  1. Zhiheng Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xianku Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Guoqing Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xianku Zhang.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Z., Zhang, X. & Zhang, G. ANFIS-based course-keeping control for ships using nonlinear feedback technique. J Mar Sci Technol 24, 1326–1333 (2019). https://doi.org/10.1007/s00773-018-0581-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00773-018-0581-z

Keywords

Search

Navigation