0
Research Papers

Modeling and Parameter Identification of an In-Tank Swimming Robot Performing Floor Inspection

[+] Author and Article Information
Imen Hbiri

National School of Engineers of Sfax,
BP 1173, Sfax 3038, Tunisia;
Digital Research Center of Sfax,
BP 275, Sfax 3021, Tunisia
e-mail: imen.hbiri@isgis.usf.tn

Houssem Karkri

National School of Engineers of Sfax,
BP 1173, Sfax 3038, Tunisia

Fathi H. Ghorbel

Department of Mechanical Engineering,
Rice University,
Houston, TX 77005
e-mail: ghorbel@rice.edu

Slim Choura

National School of Engineers of Sfax,
University of Sfax,
BP 1173, Sfax 3038, Tunisia
e-mail: slim.choura@mes.rnu.tn

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT,AND CONTROL. Manuscript received January 2, 2017; final manuscript received September 11, 2018; published online October 31, 2018. Assoc. Editor: Yang Shi.

J. Dyn. Sys., Meas., Control 141(3), 031002 (Oct 31, 2018) (10 pages) Paper No: DS-17-1001; doi: 10.1115/1.4041506 History: Received January 02, 2017; Revised September 11, 2018

In this paper, we develop the equations of motion at low-speed of a swimming robot for tank floor inspection. The proposed dynamic model incorporates a new friction drag force model for low-speed streamlined swimming robots. Based on a boundary layer theory analysis, we prove that for low-speed maneuvering case (Re from 103 to 105), the friction drag force component is nonlinear and is not insignificant, as previously considered. The proposed drag viscous model is derived based on hydrodynamic laws, validated via computational fluid dynamics (CFD) simulations, and then experimental tests. The model hydrodynamic coefficients are estimated through CFD tools. The robot wheels friction LuGre model is experimentally identified. Extensive experimental tests were conducted on the swimming robot in a circular water pool to validate the complete dynamic model. The dynamic model developed in this paper may be useful to design model-based advanced control laws required for accurate maneuverability of floor inspection swimming robots.

Copyright © 2019 by ASME
Your Session has timed out. Please sign back in to continue.

References

Griffiths, G. , 2002, Technology and Applications of Autonomous Underwater Vehicles, Vol. 2, CRC Press, New York.
Shukla, A. , and Karki, H. , 2013, “A Review of Robotics in Onshore Oil-Gas Industry,” IEEE International Conference on Mechatronics and Automation, Takamatsu, Japan, pp. 1153–1160.
Azis, F. A. , Aras, M. S. M. , Rashid, M. Z. A. , Othman, M. N. , and Abdullah, S. S. , 2012, “Problem Identification for Underwater Remotely Operated Vehicle (ROV): A Case Study,” Procedia Eng., 41, pp. 554–560. [CrossRef]
Avila, J. P. J. , and Adamowski, J. C. , 2011, “Experimental Evaluation of the Hydrodynamic Coefficients of a ROV through Morison's Equation,” Ocean Eng., 38(17–18), pp. 2162–2170. [CrossRef]
Newman, J. N. , 1977, Marine Hydrodynamics, MIT Press, Cambridge, MA.
Munson, B. R. , Rothmayer, A. P. , and Okiishi, T. H. , 2014, Fundamentals of Fluid Mechanics, 7th ed., Wiley, Hoboken, NJ.
Hoerner, S. F. , 1965, Fluid-Dynamic Drag: Practical Information on Aerodynamic Drag and Hydrodynamic Resistance, Hoerner Fluid Dynamics, Brick Town, NJ.
White, F. M. , 2010, Fluid Mechanics, 7th ed., McGraw-Hill, New York.
Fossen, T. I. , 1994, Guidance and Control of Ocean Vehicles, Wiley, New York.
Yang, H. , and Zhang, F. , 2012, “Robust Control of Formation Dynamics for Autonomous Underwater Vehicles in Horizontal Plane,” ASME J. Dyn. Syst., Meas., Control, 134(3), p. 031009. [CrossRef]
Kumar, R. P. , Dasgupta, A. , and Kumar, C. S. , 2008, “A New Tracking Controller Design for Underwater Vehicles Using Quadratic Stabilization,” ASME J. Dyn. Syst., Meas., Control, 130(2), p. 024502. [CrossRef]
Santhakumar, M. , and Kim, J. , 2014, “Robust Adaptive Tracking Control of Autonomous Underwater Vehicle-Manipulator Systems,” ASME J. Dyn. Syst., Meas., Control, 136(5), p. 054502. [CrossRef]
Ridao, P. , Tiano, A. , El-Fakdi, A. , Carreras, M. , and Zirilli, A. , 2004, “On the Identification of Non-Linear Models of Unmanned Underwater Vehicles,” Control Eng. Pract., 12(12), pp. 1483–1499. [CrossRef]
Parapari, S. , 2012, “Identification of Underwater Vehicle Hydrodynamic Coefficients Using Model Tests,” Int. J. Maritime Technol., 7(14), pp. 31–43.
Caccia, M. , Indiveri, G. , and Veruggio, G. , 2000, “Modeling and Identification of Open-Frame Variable Configuration Unmanned Underwater Vehicles,” IEEE J. Oceanic Eng., 25(2), pp. 227–240. [CrossRef]
Yuh, J. , 1990, “Modeling and Control of Underwater Robotic Vehicles,” IEEE Trans. Syst., Man, Cybern., 20(6), pp. 475–1483. https://pdfs.semanticscholar.org/9a8d/d187380033ee5b8f39b004f8b461efb70733.pdf
Yuh, J. , 1994, “Learning Control for Underwater Robotic Vehicles,” IEEE Control Syst., 14(2), pp. 39–46. [CrossRef]
Caccia, M. , and Veruggio, G. , 2000, “Guidance and Control of a Reconfigurable Unmanned Underwater Vehicle,” Control Eng. Pract., 8(1), pp. 21–37. [CrossRef]
Ridao, P. , Battle, J. , and Carreras, M. , 2001, “Model Identification of a Low-Speed UUV,” IFAC Proc., 34(7), pp. 395–400. [CrossRef]
Ross, A. , Fossen, T. I. , and Johansen, T. A. , 2004, “Identification of Underwater Vehicle Hydrodynamic Coefficients Using Free Decay Tests,” IFAC Proc. Vol., 37(10), pp. 363–368. [CrossRef]
Healey, A. J. , and Marco, D. B. , 1992, “Slow Speed Flight Control of Autonomous Underwater Vehicles: Experimental Results With NPS AUV II,” The Second International Offshore and Polar Engineering Conference, International Society of Offshore and Polar Engineers, Monterey, CA, June 14–19, pp. 523–532.
Gertler, M. , 1967, “The DTMB Planar-Motion-Mechanism System,” David W. Taylor Naval Ship Research and Development Center, Bethesda Department of Hydromechanics, Washington, DC, Report No. HML-TR-2523.
Nomoto, M. , and Hattori, M. , 1986, “A Deep ROV Dolphin 3K: Design and Performance Analysis,” IEEE J. Oceanic Eng., 11(3), pp. 373–391. [CrossRef]
Smallwood, D. A. , and Whitcomb, L. L. , 2003, “Adaptive Identification of Dynamically Positioned Underwater Robotic Vehicles,” Control Syst. Technol., IEEE Trans., 11(4), pp. 505–515. [CrossRef]
Tang, S. , Ura, T. , Nakatani, T. , Thornton, B. , and Jiang, T. , 2009, “Estimation of the Hydrodynamic Coefficients of the Complex-Shaped Autonomous Underwater Vehicle TUNA-SAND,” J. Mar. Sci. Technol., 14(3), pp. 373–386. [CrossRef]
Zhang, H. , Xu, Y. R. , and Cai, H. P. , 2010, “Using CFD Software to Calculate Hydrodynamic Coefficients,” J. Mar. Sci. Appl., 9(2), pp. 149–155. [CrossRef]
De Wit, C. C. , Olsson, H. , Astrom, K. J. , and Lischinsky, P. , 1995, “A New Model for Control of Systems With Friction,” IEEE Trans. Autom. Control, 40(3), pp. 419–425. [CrossRef]
ANSYS, 2012, “ANSYS Workbench, Release 14.5,” ANSYS, Canonsburg, PA.
Dahlby, L. M. , 2016, “Investigation of Aerodynamic Performance Predictions by CFD Using Transition Models and Comparison With Test Data,” Master's thesis, Luleå University of Technology, Luleå, Sweden
Patel, K. S. , Patel, S. B. , Patel, U. B. , and Ahuja, A. P. , 2014, “CFD Analysis of an Aerofoil,” Int. J. Eng. Res., 3(3), pp. 154–158. [CrossRef]
Chitta, V. , Walters, D. K. , and Dhakal, T. P. , 2012, Prediction of Aerodynamic Characteristics for Elliptic Airfoils in Unmanned Aerial Vehicle Applications, INTECH Open Access Publisher, Starkville, MS.
Nancy, H., 2015, “Shape Effect on Drag,” NASA Glenn Research Center, Cleveland, OH, accessed May 5, 2015, https://www.grc.nasa.gov/www/k-12/airplane/shaped.html
De Wit, C. C. , and Lischinsky, P. , 1998, “Adaptive Friction Compensation With Partially Known Dynamic Friction Model,” Int. J. Adapt. Control Signal Process., 11(1), pp. 65–80. [CrossRef]
Gagvert, M. , 2012, “Comparison of Two Friction Models,” Master thesis, Lund University, Lund, Sweden.

Figures

Grahic Jump Location
Fig. 1

An in-tank swimming robot

Grahic Jump Location
Fig. 2

Robot inspection maneuvers: (a) vertical z0 swimming path and (b) horizontal x0 − y0 path

Grahic Jump Location
Fig. 3

Robot geometry and frames

Grahic Jump Location
Fig. 4

Robot FBDs: (a) FBD for vertical swimming and (b) FBD for floor inspection

Grahic Jump Location
Fig. 5

Hydrodynamic forces: normal pressure force and tangential viscous force

Grahic Jump Location
Fig. 6

Laminar flow on a plate

Grahic Jump Location
Fig. 7

CFD simulation conditions: (a) CFD geometry, (b) computational grid, and (c) velocity field

Grahic Jump Location
Fig. 8

Curve fitting of FHvy

Grahic Jump Location
Fig. 9

Robot FBDs z-direction: (a) z-static analysis and (b) z-dynamic analysis

Grahic Jump Location
Fig. 10

Robot FBDs x-direction: (a) static analysis and (b) dynamic analysis

Grahic Jump Location
Fig. 11

Robot FBDs y-direction: (a) static analysis and (b) dynamic analysis

Grahic Jump Location
Fig. 12

Comparison of the measured and simulated plate velocities

Grahic Jump Location
Fig. 13

Velocity friction map: model response and experimental data

Grahic Jump Location
Fig. 14

Experimental setup

Grahic Jump Location
Fig. 15

Comparison of the measured and simulated robot velocities along the x-direction

Grahic Jump Location
Fig. 16

z-Induced force magnitude during surge motion

Grahic Jump Location
Fig. 17

Comparison of the measured and simulated velocities along the y-direction

Grahic Jump Location
Fig. 18

Comparison of the measured and simulated velocities along the z-direction

Grahic Jump Location
Fig. 19

Induced robot velocities u and v for the heave motion

Tables

Errata

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In