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Adaptive robust control of marine vehicles with periodic disturbance compensation: an observer-based output feedback approach

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Abstract

This work concentrates on output feedback trajectory tracking control of marine vehicles with dynamical uncertainties. The system under consideration, due to the natural response of oceanic waves, is also subject to periodic external disturbances. The output feedback structure of the proposed controller algorithm is established via a novel nonlinear model-free observer in conjunction with a Fourier series expansion-based periodic disturbance estimator. Lyapunov-based arguments have been utilized to prove the stability of the closed loop system and the convergence of tracking and unmeasured state observation errors under the closed loop operation. Performance demonstration and viability of the proposed method are realized via comparative numerical simulations.

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Notes

  1. The compact model in (5) is sometimes referred to as robot-like model due to its presentation being similar to standard robot manipulator dynamic models.

  2. In (20), the projection algorithm is used to ensure the boundedness of \(\hat{\theta }\left( t\right) \) and its time derivative since required by the subsequent stability analysis.

  3. Subscript i represents the ith entry of a column vector or the ith diagonal entry of a matrix

References

  1. Fossen TI (2002) Marine control system-guidance, navigation and control of ships, rigs and underwater vehicles. Marine Cybernetics

  2. Balchen JG, Jenssen NA, Mathisen E, Saelid S (1980) Dynamic positioning of floating vessels based on Kalman filtering and optimal control. In: IEEE Int. Conf. on Decision and Control including the Symposium on Adaptive Processes, Albuquerque, NM, USA, pp 852–864

  3. Balchen JG, Jenssen NA, Saellid S (1976) Dynamic positioning using Kalman filtering and optimal control theory. In IFAC/IFIP Symp.on Automation in Off–shore Oil Field Operation, pages 183–186, Amsterdam, Holland

  4. Grimble MJ, Patton RJ, Wise DA (1980) The design of dynamic positioning control systems using stochastic optimal control theory. Opt Control Appl Methods 1(2):167–202

    Article  Google Scholar 

  5. Sorensen AJ, Sagatun SI, Fossen TI (1996) Design of a dynamic positioning system using model-based control. Control Eng Pract 4(3):359–368

    Article  Google Scholar 

  6. AC Agostinho, Jr L Moratelli, EA Tannuri, HM Morishita (2009) Sliding mode control applied to offshore dynamic positioning systems. In Int. Conf. on Maneuvering and Control of Marine Craft, pages 237–242, Guaruj (SP), Brazil

  7. Tannuri EA, Agostinho AC (2010) Higher order sliding mode control applied to dynamic positioning systems. In Conf. on Control Applications in Marine Systems. Rostock–Waremnde, Germany, pp 132–137

  8. Li W, Sun Y, Chen H, Wang G (2017) Model predictive controller design for ship dynamic positioning system based on state-space equations. J Mar Sci Technol 22:426–431

    Article  Google Scholar 

  9. Katebi MR, Yamamoto I, Matsuura M, Grimble MJ, Hirayama H, Okamato O (2001) Robust dynamic ship positioning control system design and applications. Int J Robust Nonlinear Control 11(13):1257–1284

    Article  Google Scholar 

  10. Canudas De WC, Olguin DE, Michel P (1998) Robust nonlinear control of an underwater vehicle/manipulator system with composite dynamics. In: IEEE Int. Conf. on Robotics and Automation, Leuven, Belgium, pp 452–457

  11. Bidikli B, Tatlicioglu E, Zergeroglu E (2017) Compensating of added mass terms in dynamically positioned surface vehicles: a continuous robust control approach. Ocean Eng 139:198–204

    Article  Google Scholar 

  12. Zhang J, Sun T, Liu Z (2017) Robust model predictive control for path-following of underactuated surface vessels with roll constraints. Ocean Eng 143:125–132

    Article  Google Scholar 

  13. Wang N, Qian C, Sun JC, Liu YC (2016) Adaptive robust finite-time trajectory tracking control of fully actuated marine surface vehicles. IEEE Trans Control Syst Technol 24(4):1454–1462

    Article  Google Scholar 

  14. Zhu G, Du J (2020) Global robust adaptive trajectory tracking control for surface ships under input saturation. IEEE J Ocean Eng 45(2):442–450

    Article  Google Scholar 

  15. Hu X, Du J, Sun Y (2017) Robust adaptive control for dynamic positioning of ships. IEEE J Ocean Eng 42(4):826–835

    Article  Google Scholar 

  16. Liao Y, Jiang Q, Du T, Jiang W (2020) Redefined output model-free adaptive control method and unmanned surface vehicle heading control. IEEE J Ocean Eng 45(3):714–723

    Article  Google Scholar 

  17. Liu C, Zou Z, Yin J (2015) Trajectory tracking of underactuated surface vessels based on neural network and hierarchical sliding mode. J Mar Sci Technol 20:322–330

    Article  Google Scholar 

  18. Sun Z, Zhang G, Qiao L, Zhang W (2018) Robust adaptive trajectory tracking control of underactuated surface vessel in fields of marine practice. J Mar Sci Technol 23:950–957

    Article  Google Scholar 

  19. Bidikli B, Tatlicioglu E, Zergeroglu E (2017) Observer-based adaptive output feedback tracking control of dynamically positioned surface vessels. J Mar Sci Technol 22(2):376–387

    Article  Google Scholar 

  20. Wang N, Zhuo S, Jianchuan Y, Zaojian Z, Su SF (2019) Fuzzy unknown observer-based robust adaptive path following control of underactuated surface vehicles subject to multiple unknowns. Ocean Eng 176:57–64

    Article  Google Scholar 

  21. Lu Y, Zhang G, Qiao L, Zhang W (2020) Adaptive output-feedback formation control for underactuated surface vessels. Int J Control 93(3):400–409

    Article  MathSciNet  Google Scholar 

  22. Fjellstad O, Fossen TI (2014) Quarternion feedback regulation of underwater vehicles. In: IEEE Int. Conf. on Control Applications, Glasgow, Scotland, pp 857–862

  23. Qiao L, Zhang W (2019) Adaptive second-order fast nonsingular terminal sliding mode tracking control for fully actuated autonomous underwater vehicles. IEEE J Ocean Eng 44(2):363–385

    Article  Google Scholar 

  24. Chen Z, Zhang Y, Nie Y, Tang J, Zhu S (2020) Adaptive sliding mode control design for nonlinear unmanned surface vessel using RBFNN and disturbance-observer. IEEE Access 8:45457–45467

    Article  Google Scholar 

  25. Yu KW, Wu CE (2004) Tracking control of a ship by PI-type sliding controller. J Mar Sci Technol 12(3):183–188

    Article  Google Scholar 

  26. Du J, Hu X, Krstic M, Sun Y-Q (2018) Dynamic positioning of ships with unknown parameters and disturbances. Control Eng Pract 76:22–30

    Article  Google Scholar 

  27. Aksoy O, Zergeroglu E, Tatlicioglu E (2017) On adaptive output feedback controf robotic manipulators with online disturbance estimation. J Intell Robot Syst 85(3–4):633–649

    Article  Google Scholar 

  28. Fossen TI, Grovlen A (1998) Nonlinear output feedback control of dynamically poisitioned ships using vectorial oberver back-stepping. IEEE Trans Control Syt Technol 6(1):121–128

    Article  Google Scholar 

  29. Donaire A, Romero JG, Perez T (2017) Trajectory tracking passivity-based control for marine vehicles subject to disturbances. J Franklin Inst 354:2167–2182

    Article  MathSciNet  Google Scholar 

  30. Fu M, Yu L (2018) Finite-time extended state observer-based distributed formation control for marine surface vehicles with input saturation and disturbances. Ocean Eng 159:219–227

    Article  Google Scholar 

  31. Wang N, Sun Z, Su S-F, Wang Y (2018) Fuzzy uncertainty observer-based path-following control of underactuated marine vehicles with unmodeled dynamics and disturbances. Int J Fuzzy Syst 20(8):2593–2604

    Article  MathSciNet  Google Scholar 

  32. Du J, Hu X, Liu H, Chen CLP (2015) Adaptive robust output feedback control for a marine dynamic positioning system based on a high-gain observer. IEEE Trans Neural Netw Learn Syst 26(11):2775–2786

    Article  MathSciNet  Google Scholar 

  33. Peng Z, Wang D, Shi Y, Wang H, Wang W (2015) Containment control of networked autonomous underwater vehicles with model uncertainty and ocean disturbances guided by multiple leaders. Inf Sci 316:163–179

    Article  Google Scholar 

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Authors and Affiliations

  1. Graduate Student of the Department of Mechanical Engineering and Member of the Laboratory for Autonomy, Control, Information, and Systems (LACIS, http://lacis.eng.usf.edu/) at the University of South Florida, Tampa, FL, 33620, USA

    Deniz Kurtoglu

  2. Department of Mechatronics Engineering, Faculty of Engineering and Architecture, Izmir Katip Celebi University, Izmir, 35620, Turkey

    Baris Bidikli

  3. Department of Electrical & Electronics Engineering, Ege University, Izmir, 35100, Turkey

    Enver Tatlicioglu

  4. Department of Computer Engineering, Gebze Technical University, Gebze, 41400, Kocaeli, Turkey

    Erkan Zergeroglu

Authors
  1. Deniz Kurtoglu
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  2. Baris Bidikli
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  3. Enver Tatlicioglu
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  4. Erkan Zergeroglu
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Correspondence to Enver Tatlicioglu.

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Kurtoglu, D., Bidikli, B., Tatlicioglu, E. et al. Adaptive robust control of marine vehicles with periodic disturbance compensation: an observer-based output feedback approach. J Mar Sci Technol 27, 935–947 (2022). https://doi.org/10.1007/s00773-022-00886-6

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  • DOI: https://doi.org/10.1007/s00773-022-00886-6

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