Skip to main content

Implementation of the Ship’s Autopilot in the CPDev Environment

  • Conference paper
  • First Online:
Automation 2022: New Solutions and Technologies for Automation, Robotics and Measurement Techniques (AUTOMATION 2022)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1427))

Included in the following conference series:

  • 414 Accesses

Abstract

Ship autopilots can be divided into conventional, only capable of maintaining a given course (heading), and advanced, which can additionally keep the ship on the “path” (track) connecting the given navigation points along the route. The article presents the structure of a prototype autopilot of a ship implemented in the CPDev environment and the formulas allowing to determine the settings of the course controller (PID) and the track controller (PI) in the cascade control. For each of them, single design parameters were adopted to define the dynamics of the closed control loop. These rules were applied in the software of the autopilot prototype, created in cooperation with a Dutch company designing control and visualization systems for ships.

The author would like to thank the co-authors of the autopilot software and the entire CPDev community, in particular Leszek Trybus, Bartosz Trybus, Jan Sadolewski, Dariusz Rzonca, Andrzej Stec and Marcin Jamro.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Cimen, T., Banks, S.P.: Nonlinear optimal tracking control with application to super-tankers for autopilot design. Automatica 40, 1845–1863 (2004)

    Article  MathSciNet  Google Scholar 

  2. Dorf, R.C., Bishop, R.M.: Modern Control Systems, 11th edn. Prentice Hall, Upper Saddle River, NY (2008)

    MATH  Google Scholar 

  3. Fossen, T.I.: Guidance and Control of Ocean Vehicles, 4th edn. Wiley, Chichester (1999)

    Google Scholar 

  4. Fossen, T.I.: Marine Control Systems. Marine Cybernetics, Trondheim (2002)

    Google Scholar 

  5. Lisowski, J.: Ship as Automatic Control Plant (in Polish). Wyd. Morskie, Gdańsk (1981)

    Google Scholar 

  6. Jamro, M., et al.: CPDev engineering environment for modeling, implementation, testing, and visualization of control software. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds.) Recent Advances in Automation, Robotics and Measuring Techniques. AISC, vol. 267, pp. 81–90. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-05353-0_9

    Chapter  Google Scholar 

  7. Rzońca, D., Sadolewski, J., Stec, A., Świder, Z., Trybus, B., Trybus, L.: Mini-DCS system programming in IEC 61131-3 structured Text. J. Autom. Mob. Rob. Intell. Syst. 2(3), 48–54 (2008)

    Google Scholar 

  8. Rzońca, D., Sadolewski, J., Stec, A., Świder, Z., Trybus, B., Trybus, L.: Ship autopilot software – a case study. In: Bartoszewicz, A., Kabziński, J., Kacprzyk, J. (eds.) Advanced, Contemporary Control. AISC, vol. 1196, pp. 1499–1506. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-50936-1_124

    Chapter  Google Scholar 

  9. McCookin, E.W., Murray-Smith, D.J., Li, Y., Fossen, T.L.: Ship steering control system optimization using genetic algorithms. Control. Eng. Pract. 8, 429–443 (2000)

    Article  Google Scholar 

  10. Trybus, L.: Control Theory (in Polish). Ofic. Wyd. PRz., Rzeszów (2007)

    Google Scholar 

  11. Tzeng, C.Y., Lu, G.H.: An Internal Model Control- based Neural Network ship auto-pilot design. J. Soc. Naval Arch. Marine Eng. ROC 22(1), 13–23 (2003)

    Google Scholar 

  12. Vanec, T.W.: Fuzzy guidance controller for an autonomous boat. IEEE Control. Syst. 17(2), 43–51 (1997)

    Article  Google Scholar 

  13. Zhang, Y., Hearn, G.E., Sen, P.: A multivariable neural controller for automatic ship berthing. IEEE Control Syst. Mag. 17(4), 31–45 (1997)

    Article  Google Scholar 

  14. http://www.marinecontrol.org/Tutorial.html

Download references

Acknowledgments

This project is financed by the Minister of Education and Science of the Republic of Poland within the “Regional Initiative of Excellence” program for years 2019–2022. Project number 027/RID/2018/19, amount granted 11 999 900 PLN.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zbigniew Świder .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Świder, Z. (2022). Implementation of the Ship’s Autopilot in the CPDev Environment. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Automation 2022: New Solutions and Technologies for Automation, Robotics and Measurement Techniques. AUTOMATION 2022. Advances in Intelligent Systems and Computing, vol 1427. Springer, Cham. https://doi.org/10.1007/978-3-031-03502-9_14

Download citation

Publish with us

Policies and ethics