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Design of Fuzzy PD Depth Controller for an AUV

  • Loc, Mai Ba (Department of Mechanical and Energy System Engineering, Busan, Korea Maritime University) ;
  • Choi, Hyeung-Sik (Department of Mechanical and Energy System Engineering, Busan, Korea Maritime University) ;
  • Kim, Joon-Young (Division of Marine Equipment Engineering, Korea Maritime University) ;
  • Kim, Yong-Hwan (College of Maritime Military, Korea Maritime University) ;
  • Murakami, Ri-Ichi (Department of Mechanical Engineering, The University of Tokushima)
  • Received : 2012.12.12
  • Accepted : 2013.02.05
  • Published : 2013.02.28

Abstract

This paper presents a design of fuzzy PD depth controller for the autonomous underwater vehicle entitled KAUV-1. The vehicle is shaped like a torpedo with light weight and small size and used for marine exploration and monitoring. The KAUV-1 has a unique ducted propeller located at aft end with yawing actuation acting as a rudder. For depth control, the KAUV-1 uses a mass shifter mechanism to change its center of gravity, consequently, can control pitch angle and depth of the vehicle. A design of classical PD depth controller for the KAUV-1 was presented and analyzed. However, it has inherent drawback of gains, which is their values are fixed. Meanwhile, in different operation modes, vehicle dynamics might have different effects on the behavior of the vehicle. In this reason, control gains need to be appropriately changed according to vehicle operating states for better performance. This paper presents a self-tuning gain for depth controller using the fuzzy logic method which is based on the classical PD controller. The self-tuning gains are outputs of fuzzy logic blocks. The performance of the self-tuning gain controller is simulated using Matlab/Simulink and is compared with that of the classical PD controller.

Keywords

References

  1. Timothy Prestero, "Verification of a sixdegree of freedom simulation model for the REMUS autonomous underwater vehicle", M.S. Thesis, Massachusetts Institute of Technology, September 2001.
  2. Timothy Matthew Josserand, "Optimallyrobust nonlinear control of a class of robotic underwater vehicles", Ph.D. Dissertation, the University of Texas at Austin, December 2006.
  3. Mai Ba Loc, Hyeung-Sik Choi, et al, "Musynthesis depth controller design for a small autonomous underwater vehicle", Proc. 2nd International Symposium on Mechanical Science and Technology , Guangzhou, China, December 2011.
  4. M. Rentschler, F. Hover, C. Chryssostomidis, "Modeling and control of an Odyssey III AUV through system identification tests", 13th International Symposium on Unmanned Untethered Submersible Technology, Durham, NH, August, 2003.
  5. R. McEwen, "Modeling and control of a variable-length AUV", Tech. Rep., 2006.
  6. R. Panish, "Dynamic control capabilities and developments of the Bluefin robotics AUV fleet", Proc. 16th International Symposium on Unmanned Untethered Submersible Technology, Durham, NH, August 2009.
  7. C. Eriksen, T. Osse, et al, "Seaglider: A long-range autonomous underwater vehicle for oceanographic research," IEEE Journal of Oceanic Engineering, vol. 26, no. 4, 2001, pp. 424-436. https://doi.org/10.1109/48.972073
  8. S. A. Jenkins, D. E. Humphreys, J. Sherman, et al. "Underwater glider system study", Technical Report, Office of Naval Research, 2003.
  9. Dr. Stephen Wood, Todd Allen, et al, "The development of an autonomous underwater powered glider for deep-sea biological, chemical and physical oceanography", Proc. OCEANS 2007 - Europe, Aberdeen, UK, June 2007.
  10. Thor I. Fossen, Guidance and Control of Ocean Vehicles, John Wiley and Sons, 1994.
  11. Mai Ba Loc, Hyeung-Sik Choi, et al, "Design and control of an AUV with weight balance", Proc. Oceans'12 MTS/ IEEE Conference, Yeosu, Korea, May 2012.

Cited by

  1. Survey on Fuzzy-Logic-Based Guidance and Control of Marine Surface Vehicles and Underwater Vehicles 2017, https://doi.org/10.1007/s40815-017-0401-3