Skip to main content

Advertisement

Log in

Model-based motion control for underwater vehicle-manipulator systems with one of the three types of servo subsystems

  • Original Article
  • Published:
Artificial Life and Robotics Aims and scope Submit manuscript

Abstract

This paper deals with a motion control scheme for underwater robots equipped with manipulators. In general, for each robot, its manipulator is directly driven by electric motors with position sensors such as encoders, whereas its robot body is propelled by marine thrusters with position sensors such as inertial measurement units. It has been pointed out in the literature that for this type of underwater robots, its robot body control is more challenging than its manipulator control, because the robot body has much larger inertia, and many more inaccurate position sensors and actuators than the manipulator. Therefore, it may be practically difficult to accurately control the motion of the robot body, even if an advanced control scheme with good performance is implemented in the controller of the robot body. In this paper, we develop a model-based motion controller for the manipulator under the condition that the robot body is independently controlled by a motion controller with poor performance. Its features are to design the manipulator controller in consideration of the dynamics of the robot body including the marine thrusters as well as those of the manipulator, and to be applicable to underwater robots equipped with one of the three types of servo systems (i.e., a voltage-controlled, a torque-controlled, and a velocity-controlled servo system). Some stability properties of the control system were theoretically ensured in the stability analysis. Furthermore, these results were supported by those obtained in numerical simulations.

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

Access this article

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

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Antonelli G (2003) Underwater robots: motion and force control of vehicle-manipulator systems. Springer, Berlin

    Book  Google Scholar 

  2. Canudas de Wit C, Olguin Diaz E, Perrier M (2000) Nonlinear control of an underwater vehicle/manipulator with composite dynamics. IEEE Trans Control Syst Technol 8(6):948–960

    Article  Google Scholar 

  3. Sarkar N, Podder TK (2001) Coordinated motion planning and control of autonomous underwater vehicle-manipulator systems subject to drag optimization. IEEE J Ocean Eng 26(2):228–239

    Article  Google Scholar 

  4. Yatoh T, Sagara S, Tamura M (2008) Digital type disturbance compensation control of a floating underwater robot with 2 link manipulator. Artif Life Robot 13(1):377–381

    Article  Google Scholar 

  5. Han J, Park J, Chung WK (2011) Robust coordinated motion control of an underwater vehicle-manipulator system with minimizing restoring moments. Ocean Eng 38(10):1197–1206

    Article  Google Scholar 

  6. Santhakumar M, Kim J (2012) Indirect adaptive control of an autonomous underwater vehicle-manipulator system for underwater manipulation tasks. Ocean Eng 54:233–243

    Article  Google Scholar 

  7. Xu B, Pandian SR, Sakagami N, Petry F (2012) Neuro-fuzzy control of underwater vehicle-manipulator systems. J Franklin Inst 349(3):1125–1138

    Article  MathSciNet  Google Scholar 

  8. Taira Y, Oya M, Sagara S (2012) Adaptive control of underwater vehicle-manipulator systems using radial basis function networks. Artif Life Robot 17(1):123–129

    Article  Google Scholar 

  9. Han J, Chung WK (2014) Active use of restoring moments for motion control of an underwater vehicle-manipulator system. IEEE J Ocean Eng 39(1):100–109

    Article  Google Scholar 

  10. Esfahani HN, Azimirad V, Danesh M (2015) A time delay controller included terminal sliding mode and fuzzy gain tuning for underwater vehicle-manipulator systems. Ocean Eng 107:97–107

    Article  Google Scholar 

  11. Santhakumar M, Kim J (2015) Coordinated motion control in task space of an autonomous underwater vehicle-manipulator system. Ocean Eng 104:155–167

    Article  Google Scholar 

  12. Simetti E, Casalino G (2015) Whole body control of a dual arm underwater vehicle manipulator system. Ann Rev Control 40:191–200

    Article  Google Scholar 

  13. Taira Y, Sagara S, Oya M (2015) Robust controller with a fixed compensator for underwater vehicle-manipulator systems including thruster dynamics. Int J Adv Mechatron Syst 6(6):258–268

    Article  Google Scholar 

  14. Korkmaz O, Ider SK, Ozgoren MK (2016) Trajectory tracking control of an underactuated underwater vehicle redundant manipulator system. Asian J Control 18(5):1593–1607

    Article  MathSciNet  Google Scholar 

  15. Londhe PS, Mohan S, Patre BM, Waghmare LM (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 

  16. Haugalokken BOA, Jorgensen EK, Schjolberg I (2018) Experimental validation of end-effector stabilization for underwater vehicle-manipulator systems in subsea operations. Robot Auton Syst 109:1–12

    Article  Google Scholar 

  17. Choi HS (1996) Modeling of robot manipulators working under the sea and the design of a robust controller. Robotica 14(2):213–218

    Article  Google Scholar 

  18. Lee M, Choi HS (2000) A robust neural controller for underwater robot manipulators. IEEE Trans Neural Netw 11(6):1465–1470

    Article  Google Scholar 

  19. Yuh J, Zhao S, Lee PM (2001) Application of adaptive disturbance observer control to an underwater manipulator. In: Proceedings of the 2001 IEEE international conference on robotics and automation, pp 3244–3249

  20. Kim J, Chung WK, Yuh J (2003) Dynamic analysis and two-time scale control for underwater vehicle-manipulator systems. In: Proceedings of the 2003 IEEE/RSJ international conference on intelligent robots and systems, pp 577–582

  21. Yoerger DR, Cooke JG, Slotine JJE (1990) The influence of thruster dynamics on underwater vehicle behavior and their incorporation into control system design. IEEE J Ocean Eng 15(3):167–178

    Article  Google Scholar 

  22. Taira Y, Sagara S, Oya M (2018) Design of a motion controller for an underwater vehicle-manipulator system with a differently-controlled vehicle. In: Proceedings of the international conference on information and communication technology robotics, Paper No. FA1.2, pp 1–6

  23. Taira Y, Sagara S, Oya M (2019) Design of two types of kinematic control for an underwater vehicle-manipulator system with a differently-controlled vehicle. In: Proceedings of the 24th international symposium on artificial life and robotics, pp 1015–1020

  24. Craig JJ (2005) Introduction to robotics: mechanics and control, 3rd edn. Prentice Hall, Upper Saddle River

    Google Scholar 

  25. Arimoto S (1996) Control theory of nonlinear-mechanical systems: a passivity-based and circuit-theoretic approach. Oxford University Press, New York

    MATH  Google Scholar 

  26. Canudas de Wit C, Siciliano B, Bastin G (eds) (1996) Theory of robot control. Springer, London

    MATH  Google Scholar 

  27. Horn RA, Johnson CR (2013) Matrix analysis, 2nd edn. Cambridge University Press, New York

    MATH  Google Scholar 

  28. Krstic M, Kanellakopoulos I, Kokotovic P (1995) Nonlinear and adaptive control design. Wiley, New York

    MATH  Google Scholar 

  29. Ioanou PA, Sun J (1996) Robust adaptive control. Prentice Hall, Upper Saddle River

    Google Scholar 

  30. Taia Y, Sagara S, Oya M (2018) Motion and force control with a nonlinear force error filter for underwater vehicle-manipulator systems. Artif Life Robot 23(1):103–117

    Article  Google Scholar 

  31. Kim J, Chung WK (2006) Accurate and practical thruster modeling for underwater vehicle. Ocean Eng 33(5–6):566–586

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yuichiro Taira.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This work was presented in part at the 24th International Symposium on Artificial Life and Robotics Beppu, Oita, January 23–25, 2019.

Appendices

Appendix 1: Derivation of (5)

For simplicity, we express \(\exp (\cdot )\) as \({e}^{(\cdot )}\) in this appendix. Substituting the second equation of (3) into the time derivative of the first equation of (3), we have

$$\begin{aligned} \dot{f}_{V}(\cdot )=\, & {} [\dot{T}(\cdot )-T(\phi _{V})C_{1}D(v)] C_{3}D(v)v(t) \nonumber \\&+T(\phi _{V})C_{2}C_{3} D(v)\tau _{V}(t). \end{aligned}$$
(90)

In the derivation of (90), we use the differential relation \(d\{ D(v)v(t)\} /dt =2D(v)\dot{v}(t)\). Substituting (90) into the time derivative of (2), we obtain

$$\begin{aligned}&d\{ M_{V}(\phi ) \ddot{x}_{V}(t) \} /dt +d\{ M_{VM}(\phi ) \ddot{q}(t)\} /dt \nonumber \\&\qquad +d\{ n_{V}(\cdot )+d_{V}(t)\} /dt \nonumber \\&\quad =[ \dot{T}(\cdot )-T(\phi _{V})C_{1} D(v)] C_{3}D(v)v(t) \nonumber \\&\qquad +T(\phi _{V})C_{2}C_{3}D(v)\tau _{V}(t). \end{aligned}$$
(91)

Replacing the symbol t by the symbol \(\bar{\tau }\) in (91), then multiplying both its sides by \({e}^{-\rho (t-\bar{\tau })}\), and then integrating both its sides from 0 to t with respect to \(\bar{\tau }\), we have

$$\begin{aligned} s_{V1}(t)+s_{V2}(t)+s_{V3}(t)=s_{V4}(t) \end{aligned}$$
(92)
$$\begin{aligned} s_{V1}(t)= & {} \int _{0}^{t} {e}^{-\rho (t-\bar{\tau })} [ d\{ M_{V}(\phi (\bar{\tau })) \ddot{x}_{V}(\bar{\tau }) \} /d\bar{\tau } ] d\bar{\tau } \nonumber \\ s_{V2}(t)= & {} \int _{0}^{t} {e}^{-\rho (t-\bar{\tau })} [ d\{ M_{VM}(\phi (\bar{\tau })) \ddot{q}(\bar{\tau })\} /d\bar{\tau } ] d\bar{\tau } \nonumber \\ s_{V3}(t)= & {} \int _{0}^{t} {e}^{-\rho (t-\bar{\tau })} [ d\{ n_{V}(\phi (\bar{\tau }),\dot{\varphi }(\bar{\tau })) \nonumber \\&+d_{V}(\bar{\tau }) \} /d\bar{\tau } ] d\bar{\tau } \nonumber \\ s_{V4}(t)= & {} \int _{0}^{t} {e}^{-\rho (t-\bar{\tau })} \{ [ \dot{T}(\phi _{V}(\bar{\tau }),\dot{\phi }_{V}(\bar{\tau })) \nonumber \\&-T(\phi _{V}(\bar{\tau }))C_{1} D(v(\bar{\tau }))] C_{3}D(v(\bar{\tau }))v(\bar{\tau }) \nonumber \\&+T(\phi _{V}(\bar{\tau }))C_{2}C_{3}D(v(\bar{\tau }))\tau _{V}(\bar{\tau }) \} d\bar{\tau }. \end{aligned}$$
(93)

It should be noted that this operation is equivalent to applying the stable first-order filter \(1/(s+\rho )[\, \cdot \,]\) to (91). Applying the integration by parts to the first equation of (93), we have

$$\begin{aligned} s_{V1}(t)=\, & {} M_{V}(\phi )\ddot{x}_{V}(t)-{e}^{-\rho t} M_{V}(\phi (0))\ddot{x}_{V}(0)\nonumber \\&-\rho {e}^{-\rho t} \int _{0}^{t} {e}^{\rho \bar{\tau }} M_{V} (\phi (\bar{\tau })) \ddot{x}_{V}(\bar{\tau })d\bar{\tau }. \end{aligned}$$
(94)

Reapplying the integration by parts to (94), we obtain

$$\begin{aligned} s_{V1}(t)=\, & {} M_{V}(\phi )\ddot{x}_{V}(t)-\rho M_{V}(\phi )\dot{x}_{V}(t)\nonumber \\&+{e}^{-\rho t} [ - M_{V}(\phi (0))\ddot{x}_{V}(0)+\rho M_{V}(\phi (0))\dot{x}_{V}(0)] \nonumber \\&+\rho \int _{0}^{t} {e}^{-\rho (t-\bar{\tau })} [ \rho M_{V} (\phi (\bar{\tau })) \nonumber \\&+\dot{M}_{V}(\phi (\bar{\tau }),\dot{\phi }(\bar{\tau })) ] \dot{x}_{V}(\bar{\tau }) d\bar{\tau }. \end{aligned}$$
(95)

In a way similar to the derivation of (95), we can rewrite the second equation of (93) as

$$\begin{aligned} s_{V2}(t)=\, & {} M_{VM}(\phi )\ddot{q}(t)-\rho M_{VM}(\phi )\dot{q}(t)\nonumber \\&+{e}^{-\rho t} [ - M_{VM}(\phi (0))\ddot{q}(0)+\rho M_{VM}(\phi (0))\dot{q}(0)] \nonumber \\&+\rho \int _{0}^{t} {e}^{-\rho (t-\bar{\tau })} [ \rho M_{VM} (\phi (\bar{\tau })) \nonumber \\&+\dot{M}_{VM}(\phi (\bar{\tau }),\dot{\phi }(\bar{\tau })) ] \dot{q}(\bar{\tau }) d\bar{\tau }. \end{aligned}$$
(96)

Applying the integration by parts to the third equation of (93), we have

$$\begin{aligned} s_{V3}(t)=\, & {} n_{V}(\phi ,\dot{\varphi })+d_{V}(t)\nonumber \\&-{e}^{-\rho t} [ n_{V}(\phi (0),\dot{\varphi }(0))+d_{V}(0)] \nonumber \\&-\rho \int _{0}^{t} {e}^{-\rho (t-\bar{\tau })} [ n_{V}(\phi (\bar{\tau }),\dot{\varphi }(\bar{\tau }))+d_{V}(\bar{\tau }) ] d\bar{\tau }. \end{aligned}$$
(97)

Substituting (93) (the fourth equation) and (95) to (97) into (92), and then considering the fact that the first-order filters (7) have the solution

$$\begin{aligned} w_{VF1}(t)=\, & {} {e}^{-\rho t} w_{VF10} \nonumber \\ w_{VF2}(t)= & {} -\rho \int _{0}^{t} {e}^{-\rho (t-\bar{\tau })} d_{V}(\bar{\tau }) d\bar{\tau } \nonumber \\ z_{VF}(t)= & {} \int _{0}^{t} {e}^{-\rho (t-\bar{\tau })} \{ \rho [ \rho M_{V}(\phi (\bar{\tau })) \nonumber \\&+\dot{M}_{V}(\phi (\bar{\tau }),\dot{\phi }(\bar{\tau })) ] \dot{x}_{V}(\bar{\tau })+\rho [ \rho M_{VM}(\phi (\bar{\tau })) \nonumber \\&+\dot{M}_{VM}(\phi (\bar{\tau }),\dot{\phi }(\bar{\tau })) ] \dot{q}(\bar{\tau }) -\rho n_{V}(\phi (\bar{\tau }),\dot{\varphi }(\bar{\tau })) \nonumber \\&-[ \dot{T}(\phi _{V}(\bar{\tau }),\dot{\phi }_{V}(\bar{\tau })) \nonumber \\&-T(\phi _{V}(\bar{\tau }))C_{1}D(v(\bar{\tau }))] C_{3} D(v(\bar{\tau })) v(\bar{\tau }) \nonumber \\&-T(\phi _{V}(\bar{\tau }))C_{2}C_{3}D(v(\bar{\tau }))\tau _{V}(\bar{\tau })\} d\bar{\tau }, \end{aligned}$$
(98)

we obtain the model (5). In this derivation, we use (6).

Appendix 2: Derivations of (21) and (23)

For simplicity, we express \(\exp (\cdot )\) as \({e}^{(\cdot )}\) in this appendix. Using the first equation of (6), we can write the norm of \(z_{C}(t)\) as

$$\begin{aligned} \Vert z_{C}(t) \Vert\le & {} c_{N1}+(c_{M1}+c_{M2}) \rho \Vert \dot{\varphi }(t) \Vert +c_{N2} \Vert \dot{\varphi }(t) \Vert ^{2} \nonumber \\&+\Vert z_{VF}(t) \Vert . \end{aligned}$$
(99)

In the derivation of (99), we utilize (17) (the first and second inequalities), (19) (the first inequality), and the inequalities \(\Vert \dot{q}(t) \Vert \le \Vert \dot{\varphi }(t) \Vert\) and \(\Vert \dot{x}_{V}(t) \Vert \le \Vert \dot{\varphi }(t) \Vert\). Using the solution of the third differential equation of (7) [i.e., the third equation of (98)], we can write the norm of \(z_{VF}(t)\) as

$$\begin{aligned} \Vert z_{VF}(t) \Vert\le & {} \bar{c}_{VF1} \int _{0}^{t} {e}^{-\rho (t-\bar{\tau })} [ \rho +\rho ^{2} \Vert \dot{\varphi } (\bar{\tau }) \Vert \nonumber \\&\quad +\rho \Vert \dot{\varphi } (\bar{\tau }) \Vert ^{2}+\Vert \dot{\varphi } (\bar{\tau }) \Vert \Vert v(\bar{\tau }) \Vert ^{2} +\Vert v(\bar{\tau }) \Vert ^{3} \nonumber \\&\quad +\Vert v(\bar{\tau }) \Vert \Vert \tau _{V}(\bar{\tau }) \Vert ] d\bar{\tau } \end{aligned}$$
(100)

where \(\bar{c}_{VF1} \in R^{+}\) is given by

$$\begin{aligned} \bar{c}_{VF1}= & {} \max \{ c_{N1},c_{M1}+c_{M2},c_{M4}+c_{M5}+c_{N2}, \nonumber \\&c_{T2}c_{V1}\Vert C_{3} \Vert , c_{T1}c_{V1}^{2}\Vert C_{1} \Vert \Vert C_{3} \Vert , c_{T1}c_{V1}\Vert C_{2}C_{3} \Vert \}. \nonumber \\ \end{aligned}$$
(101)

In the derivation of (100), we utilize (17) (the first, second, fourth, and fifth inequalities), (19) (the first inequality), (20), and the inequalities \(\Vert \dot{x}_{V}(t) \Vert \le \Vert \dot{\varphi }(t) \Vert\) and \(\Vert \dot{q}(t) \Vert \le \Vert \dot{\varphi }(t) \Vert\). In view of the fact that the time integral in (100) is equivalent to the solution of the first-order differential equation (22), we can rewrite the inequality (100) as

$$\begin{aligned} \Vert z_{VF}(t) \Vert \le \bar{c}_{VF1} z_{QF}(t). \end{aligned}$$
(102)

Applying (102) to (99), we have

$$\begin{aligned} \Vert z_{C}(t) \Vert\le\, & {} c_{N1}+(c_{M1}+c_{M2}) \rho \Vert \dot{\varphi }(t) \Vert +c_{N2} \Vert \dot{\varphi }(t) \Vert ^{2} \nonumber \\&+\bar{c}_{VF1} z_{QF}(t). \end{aligned}$$
(103)

Furthermore, applying (103) to the norm of \(z_{Q}(t)\) [given by the second equation of (12)], we obtain

$$\begin{aligned} \Vert z_{Q}(t) \Vert\le & {} c_{M2}c_{M7}c_{N1}+c_{N3}+c_{M2}c_{M7}(c_{M1} \nonumber \\&+c_{M2}) \rho \Vert \dot{\varphi }(t) \Vert + (c_{N4}+c_{M2}c_{M7}c_{N2}) \Vert \dot{\varphi }(t) \Vert ^{2}\nonumber \\&+c_{M2}c_{M7}\bar{c}_{VF1}z_{QF}(t), \end{aligned}$$
(104)

and we can directly obtain (21) from (104). In the derivation of (104), we utilize (17) (the second and seventh inequalities) and (19) (the second inequality).

In view of the condition that the disturbances \(d_{V}(t)\) and \(d_{M}(t)\) are bounded, we obtain the inequalities

$$\begin{aligned} \Vert d_{V}(t) \Vert \le c_{D1},\; \Vert d_{M}(t) \Vert \le c_{D2} \end{aligned}$$
(105)

where \(c_{D1}\) and \(c_{D2}\) are positive constants. Using the second equation of (6), we can write the norm of \(w_{C}(t)\) as

$$\begin{aligned} \Vert w_{C}(t) \Vert \le c_{D1}+\Vert w_{VF1}(t) \Vert +\Vert w_{VF2}(t) \Vert . \end{aligned}$$
(106)

In the derivation of (106), we utilize the first inequality of (105). Using the solution of the first differential equation of (7) [i.e., the first equation of (98)], we can write the norm of \(w_{VF1}(t)\) as

$$\begin{aligned} \Vert w_{VF1}(t) \Vert \le \Vert w_{VF10} \Vert . \end{aligned}$$
(107)

Similarly, using the solution of the second differential equation of (7) [i.e., the second equation of (98)], we can write the norm of \(w_{VF2}(t)\) as

$$\begin{aligned} \Vert w_{VF2}(t) \Vert \le c_{D1}. \end{aligned}$$
(108)

In the derivation of (108), we utilize the first inequality of (105). Applying (107) and (108) to (106), we obtain

$$\begin{aligned} \Vert w_{C}(t) \Vert \le 2c_{D1}+\Vert w_{VF10} \Vert . \end{aligned}$$
(109)

Furthermore, using the third inequality of (12), we can write the norm of \(w_{Q}(t)\) as

$$\begin{aligned} \Vert w_{Q}(t) \Vert \le c_{D2}+2c_{D1}c_{M2}c_{M7}+c_{M2}c_{M7}\Vert _{VF10} \Vert , \end{aligned}$$
(110)

and we can directly obtain (23) from (110). In the derivation of (110), we utilize (17) (the second and seventh inequalities), (105) (the second inequality), and (109).

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Taira, Y., Sagara, S. & Oya, M. Model-based motion control for underwater vehicle-manipulator systems with one of the three types of servo subsystems. Artif Life Robotics 25, 133–148 (2020). https://doi.org/10.1007/s10015-019-00564-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10015-019-00564-8

Keywords

Navigation

pFad - Phonifier reborn

Pfad - The Proxy pFad of © 2024 Garber Painting. All rights reserved.

Note: This service is not intended for secure transactions such as banking, social media, email, or purchasing. Use at your own risk. We assume no liability whatsoever for broken pages.


Alternative Proxies:

Alternative Proxy

pFad Proxy

pFad v3 Proxy

pFad v4 Proxy