Skip to main content

Advertisement

SpringerLink
Log in

Design of super twisting disturbance observer based control for autonomous underwater vehicle

  • Published:
International Journal of Dynamics and Control Aims and scope Submit manuscript

Abstract

Autonomous underwater vehicles (AUVs) operates in uncertain oceanic environment with unknown external non-vanishing disturbances such as ocean currents. To handle such uncertainties, a super twisting algorithm as a disturbance observer based sliding mode controller (STA-SMC) is designed for trajectory tracking of a linearised steering and diving plane models of highly non-linear model of AUV. The efficacy of designed control scheme has been verified by comparing it with uncertainty and disturbance estimator (UDE) and disturbance observer (DO) based sliding mode control strategies. The extensive numerical simulations have been performed to demonstrate the robustness of the proposed scheme. It is found that the proposed STA-SMC scheme is not only effective in compensating the uncertainties in hydrodynamic parameters of the vehicle but also it rejects unpredictable disturbances due to fast and high magnitude underwater ocean currents. The stability of the designed observer based control scheme is provided by Lyapunov theory.

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

Similar content being viewed by others

References

  1. Krogstad and Arntsen, “Linear wave theory,” Part A, Norwegian University of Science and Technology, Trondheim, Norway

  2. Jalving B (1994) The ndre-auv flight control system. IEEE J Oceanic Eng 19(4):497–501

    Article  Google Scholar 

  3. Yoerger D, Slotine J (1985) Robust trajectory control of underwater vehicles. IEEE J Oceanic Eng 10(4):462–470

    Article  Google Scholar 

  4. Joe H, Kim M, Yu S-C (2014) Second-order sliding-mode controller for autonomous underwater vehicle in the presence of unknown disturbances. Nonlinear Dyn 78(1):183–196

    Article  Google Scholar 

  5. Pisano A, Usai E (2004) Output-feedback control of an underwater vehicle prototype by higher-order sliding modes. Automatica 40(9):1525–1531

    Article  MathSciNet  Google Scholar 

  6. Bessa WM, Dutra MS, Kreuzer E (2010) An adaptive fuzzy sliding mode controller for remotely operated underwater vehicles. Robot Auton Syst 58(1):16–26

    Article  Google Scholar 

  7. Ramezani-al MR, Sereshki ZT (2019) A novel adaptive sliding mode controller design for tracking problem of an auv in the horizontal plane. Int J Dyn Control 7(2):679–689

    Article  MathSciNet  Google Scholar 

  8. Londhe PS, Santhakumar M, Patre BM, Waghmare LM (2016) Task space control of an autonomous underwater vehicle manipulator system by robust single-input fuzzy logic control scheme. IEEE J Oceanic Eng 42(1):13–28

    Google Scholar 

  9. Lakhekar G, Waghmare L, Vaidyanathan S (2016) “Diving autopilot design for underwater vehicles using an adaptive neuro-fuzzy sliding mode controller,” In: Advances and applications in nonlinear control systems, pp 477–503, Springer

  10. Londhe P, Mohan S, Patre B, Waghmare L (2017) Robust task-space control of an autonomous underwater vehicle-manipulator system by pid-like fuzzy control scheme with disturbance estimator. Ocean Eng 139:1–13

    Article  Google Scholar 

  11. Lakhekar G, Waghmare LM (2017) Robust maneuvering of autonomous underwater vehicle: an adaptive fuzzy pi sliding mode control. Intel Serv Robot 10(3):195–212

    Article  Google Scholar 

  12. Londhe P, Patre B (2019) Adaptive fuzzy sliding mode control for robust trajectory tracking control of an autonomous underwater vehicle. Intel Serv Robot 12(1):87–102

    Article  Google Scholar 

  13. Venugopal K, Sudhakar R, Pandya A (1992) On-line learning control of autonomous underwater vehicles using feedforward neural networks. IEEE J Oceanic Eng 17(4):308–319

    Article  Google Scholar 

  14. Patre B, Londhe P, Waghmare L, Mohan S (2018) Disturbance estimator based non-singular fast fuzzy terminal sliding mode control of an autonomous underwater vehicle. Ocean Eng 159:372–387

    Article  Google Scholar 

  15. Londhe P, Dhadekar DD, Patre B, Waghmare L (2017) Uncertainty and disturbance estimator based sliding mode control of an autonomous underwater vehicle. Int J Dyn Control 5(4):1122–1138

    Article  MathSciNet  Google Scholar 

  16. Guerrero J, Torres J, Creuze V, Chemori A (2020) Adaptive disturbance observer for trajectory tracking control of underwater vehicles. Ocean Eng 200:107080

    Article  Google Scholar 

  17. Lakhekar GV, Waghmare LM, Roy RG (2019) Disturbance observer-based fuzzy adapted s-surface controller for spatial trajectory tracking of autonomous underwater vehicle. IEEE Trans Intell Veh 4(4):622–636

    Article  Google Scholar 

  18. Han L, Tang G, Xu R, Huang H, Xie D (2020) “Tracking control of an underwater manipulator using fractional integral sliding mode and disturbance observer,” Transactions of the Canadian Society for Mechanical Engineering, no. ja

  19. Li J, Huang H, Wan L, Zhou Z, Xu Y (2019) Hybrid strategy-based coordinate controller for an underwater vehicle manipulator system using nonlinear disturbance observer. Robotica 37(10):1710–1731

    Article  Google Scholar 

  20. Levant A (1993) Sliding order and sliding accuracy in sliding mode control. Int J Control 58(6):1247–1263

    Article  MathSciNet  Google Scholar 

  21. Utkin VI, Poznyak AS (2013) Adaptive sliding mode control with application to super-twist algorithm: Equivalent control method. Automatica 49(1):39–47

    Article  MathSciNet  Google Scholar 

  22. Chalanga A, Kamal S, Fridman LM, Bandyopadhyay B, Moreno JA (2016) Implementation of super-twisting control: Super-twisting and higher order sliding-mode observer-based approaches. IEEE Trans Industr Electron 63(6):3677–3685

    Article  Google Scholar 

  23. Yan R, Wu Z (2019) Super-twisting disturbance observer-based finite-time attitude stabilization of flexible spacecraft subject to complex disturbances. J Vib Control 25(5):1008–1018

    Article  MathSciNet  Google Scholar 

  24. Fossen TI et al (1994) Guidance and control of ocean vehicles, vol 199. Wiley, New York

    Google Scholar 

  25. SNAME T (1950) “Nomenclature for treating the motion of a submerged body through a fluid,” The society of naval architects and marine engineers, technical and research bulletin no, pp 1–5

  26. Healey AJ, Lienard D (1993) Multivariable sliding mode control for autonomous diving and steering of unmanned underwater vehicles. IEEE J Oceanic Eng 18(3):327–339

    Article  Google Scholar 

  27. Chalanga A, Kamal S, Bandyopadhyay B (2014) A new algorithm for continuous sliding mode control with implementation to industrial emulator setup. IEEE/ASME Trans Mechatron 20(5):2194–2204

    Article  Google Scholar 

  28. Zhong Q-C, Rees D (2004) Control of uncertain lti systems based on an uncertainty and disturbance estimator. J Dyn Syst Meas Contr 126(4):905–910

    Article  Google Scholar 

  29. Dhadekar DD, Talole S (2018) Robust fault tolerant longitudinal aircraft control. IFAC-PapersOnLine 51(1):604–609

    Article  Google Scholar 

  30. Suryawanshi PV, Shendge PD, Phadke SB (2016) A boundary layer sliding mode control design for chatter reduction using uncertainty and disturbance estimator. Int J Dyn Control 4(4):456–465

    Article  MathSciNet  Google Scholar 

  31. Moreno JA, Osorio M (2012) Strict lyapunov functions for the super-twisting algorithm. IEEE Trans Autom Control 57(4):1035–1040

    Article  MathSciNet  Google Scholar 

  32. Langlois N, Guermouche M, Ali SA, Ali MGSA (2015) Super-twisting algorithm for dc motor position control via disturbance observer. IFAC-PapersOnLine 48(30):43–48

    Article  Google Scholar 

  33. Valeriano-Medina Y, Martinez A, Hernandez L, Sahli H, Rodriguez Y, Cañizares JR (2013) Dynamic model for an autonomous underwater vehicle based on experimental data. Math Computer Modell Dyn Syst 19(2):175–200

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Instrumentation Engineering, S.G.G.S. Institute of Engineering and Technology, Nanded, Maharashtra, India

    S. S. Nerkar & B. M. Patre

  2. Department of Instrumentation Engineering, Government College of Engineering, Chandrapur, Maharashtra, India

    P. S. Londhe

Authors
  1. S. S. Nerkar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. P. S. Londhe
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. B. M. Patre
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to B. M. Patre.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nerkar, S.S., Londhe, P.S. & Patre, B.M. Design of super twisting disturbance observer based control for autonomous underwater vehicle. Int. J. Dynam. Control 10, 306–322 (2022). https://doi.org/10.1007/s40435-021-00797-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40435-021-00797-1

Keywords

Search

Navigation