Fuzzy Waypoint Guidance Controller for Underactuated Catamaran Wave Adaptive Modular Vessel

  • Jyotsna Pandey
  • Kazuhiko Hasegawa
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 751)


The development of a GPS based position control system for Wave Adaptive Modular Vessel (WAM-V) able to navigate between waypoints is discussed in this chapter. A fuzzy reasoned double loop controller is proposed for navigation path planning of WAM-V. For outer loop fuzzy controller is used to feed the desired heading to the inner loop. In the inner loop, a PID feedback controller is used to correct the desired course generated by the fuzzy reasoned algorithm. The control system provides the required feedback signals to track the desired heading which is obtained from the fuzzy algorithm. After PID generates the appropriate command, the thrust isallocated to the port side and starboard side thrusters along with the command from lookup table. Using the proposed controller, several experiments are conducted at Osaka University free running pond facility. The WAM-V is equipped without rudder, thus it is driven by a combination of different thrusts to control both speed and heading. Several experimental results with different sets of waypoint validate the proposed algorithm. The obtained results affirmed that the proposed fuzzy waypoint guidance control algorithm is powerful to realize the navigation path planning. The waypoint navigation experimental results show that the fuzzy guided waypoint controller scheme is simple, intelligent and robust. The goal of this research is to present a solution to the waypoint control problem for the underactuated catamaran vessel (WAM-V), which is achieved successfully.


Navigation system Waypoint guidance Fuzzy logic Marine robotics Underactuated catamaran vessel 


  1. Ahmed, Y.A., Hasegawa, K.: Fuzzy reasoned waypoint controller for automatic ship guidance. In: 10th International Federation of Automatic Control—CAMS, vol. 49, issue 23, pp. 604–609 (2016)Google Scholar
  2. Amerongen, J.V., Naute Lenke, H.R., Veen der Van, J.C.T.: An autopilot for ships designed by with fuzzy sets. Proc. IFAC Conference on Digital Computer Applications to Process Control, The Hague, pp. 479–487 (1977)Google Scholar
  3. Beard, R.W., Maclain T.W.: Small Unmanned Aircraft Theory and Practice. Princeton University Press (2012)Google Scholar
  4. Cheng, J., Yi, J.: A new fuzzy Autopilot for way-point tracking control of ships, pp. 451–456. IEEE—ICFS, Canada (2006)Google Scholar
  5. COLREGs—convention on the international regulations for preventing collisions at sea. International Maritime Organization (IMO) (1972)Google Scholar
  6. Driankov, D., Hellendoorn, H., Reinfrank, M.: An Introduction to Fuzzy Control, 2nd edn. Springer-Verlag, Berlin (1996)CrossRefzbMATHGoogle Scholar
  7. Faltinsen, O.M.: Hydrodynamics of High-Speed Marine Vehicles. Cambridge University Press (2005)Google Scholar
  8. Fossen, T.I.: Guidance and Control of Ocean Vehicles. Wiley, New York (1994)Google Scholar
  9. Fossen, T.I., Johansen, T.A.: A survey of Control Allocation method for Ships and Underwater Vehicles. In: MED 06 14th, Italy (2006)Google Scholar
  10. Hasegawa, K. et al.: Ship auto-navigation fuzzy expert system (SAFES). J. Soc. Naval Archit. Jpn. 445–452 (1986)Google Scholar
  11. Hasegawa, K.: Automatic navigator-included simulation for narrow and congested waterways. In: Proceedings of Ninth Ship Control Systems Symposium, vol. 2, pp. 110–134 (1990)Google Scholar
  12. Hasegawa, K.: Knowledge-based automatic navigation system for harbour manoeuvring. In: Proceedings of 10th Ship Control System Symposium, vol. 2, pp. 67–90 (1993)Google Scholar
  13. Inoue, S., Hirano, M., Kijima, K., Takashima, J.: A Practical Calculation Method of Ship Maneuvering Motion, vol. 28, no. 325. ISP (1981)Google Scholar
  14. Jia, B., et al.: Design and Stability Analysis of Fuzzy Switched PID controller for Ship Track Keeping. J. Transp. Technol. 2, 334–338 (2012)CrossRefGoogle Scholar
  15. Lee, S.M., et al.: A Fuzzy Logic for Autonomous Navigation of Marine Vehicles Satisfying COLREG Guidelines. Int. J. Control Autom. Syst. 2(2), 171–181 (2004)Google Scholar
  16. Maritime Advanced Research Inc. Wave Adaptive Multipurpose Vessel.
  17. Motora, S.: On the measurement of added mass and added moment of inertia for ship motions (Part 1, 2 and 3). J. SNAJ 105, 106 (1959, 1960). (In Japanese)Google Scholar
  18. Oh, S.R., Sun, J.: Path following of underactuated marine surface vessels using line-of-sight based model predictive control. Ocean Eng. 289–295 (2010). ElsevierGoogle Scholar
  19. Ogawa, A., Koyama, T., Kijima, K.: MMG report on the mathematical model of ship manoeuvring. Bull. Soc. Naval Archit. Jpn. 575–28 (1977). (in Japanese)Google Scholar
  20. Ogawa, A., Kasai, H.: On the mathematical model of manoeuvring motion of ships. Int. Shipbuild. Prog. 25(292), 306–319 (1978a)CrossRefGoogle Scholar
  21. Ogawa, A., Kasai, H.: On the mathematical model of manoeuvring motion of ships. Int. Shipbuild. Prog. 25(292), 306–319 (1978b)CrossRefGoogle Scholar
  22. Pandey, J., Hasegawa, K.: Study on Manoeuverability and control of an autonomous wave adaptive modular vessel (WAM-V) for ocean observation. In: IAIN World Congress. IEEE (2015)Google Scholar
  23. Pandey, J., Hasegawa, K.: Study on turning manoeuvre of catamaran surface vessel with a combined experimental and simulation method. In: 10th IFAC Conference on Control Applications in Marine System CAMS, vol. 49, issue 23, pp. 446–451 (2016a)Google Scholar
  24. Pandey, J., Hasegawa, K.: Path following of underactuated catamaran surface vessel (WAM-V) using fuzzy waypoint guidance algorithm. In: IEEE Intellisys, pp. 995–1000 (2016b)Google Scholar
  25. Pandey, J., Hasegawa, K.: Manoeuvring mathematical model of catamaran wave adaptive modular vessel (WAM-V) using the system identification technique. In: Proceedings of 7th PAAMES and Advance Maritime Engineering Conference, 2016 13–14 October, Hong Kong, pp. 1–6 (2016c)Google Scholar
  26. Sanjay, N., et al.: Performance Analysis of Ship tracking using PID/Fuzzy controller. IJCTT 6, 1858–1861 (2013)Google Scholar
  27. Yasukawa, H., Yoshimura, Y.: Introduction of MMG standard method for ship manoeuvring predictions. JASNAOE 20, 37–52 (2015)Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Graduate School of EngineeringOsaka UniversitySuita, OsakaJapan
  2. 2.Division of Global Architecture, Department of Naval Architecture & Ocean EngineeringSuita, OsakaJapan

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