SCIENCE CHINA Information Sciences, Volume 63 , Issue 1 : 112207(2020) https://doi.org/10.1007/s11432-019-1470-x

Unscented Kalman-filter-based sliding mode control for an underwater gliding snake-like robot

More info
  • ReceivedApr 22, 2019
  • AcceptedJul 10, 2019
  • PublishedDec 24, 2019



This work was supported by National Key Research and Development Project of China (Grant No. 2017YFB1300101).


[1] Gomáriz S, Masmitjà I, González J. GUANAY-II: an autonomous underwater vehicle for vertical/horizontal sampling. J Mar Sci Technol, 2015, 20: 81-93 CrossRef Google Scholar

[2] Chen C W, Jiang Y, Huang H C. Computational fluid dynamics study of the motion stability of an autonomous underwater helicopter. Ocean Eng, 2017, 143: 227-239 CrossRef Google Scholar

[3] Webb D C, Simonetti P J, Jones C P. SLOCUM: an underwater glider propelled by environmental energy. IEEE J Ocean Eng, 2001, 26: 447-452 CrossRef ADS Google Scholar

[4] Sherman J, Davis R E, Owens W B. The autonomous underwater glider “Spray”. IEEE J Ocean Eng, 2001, 26: 437-446 CrossRef ADS Google Scholar

[5] Eriksen C C, Osse T J, Light R D. Seaglider: a long-range autonomous underwater vehicle for oceanographic research. IEEE J Ocean Eng, 2001, 26: 424-436 CrossRef Google Scholar

[6] Yu J, Zhang A, Jin W. Development and experiments of the Sea-Wing underwater glider. China Ocean Eng, 2011, 25: 721-736 CrossRef ADS Google Scholar

[7] Katzschmann R K, Marchese A D, Rus D. Hydraulic autonomous soft robotic fish for 3D swimming. In: Experimental Robotics. Berlin: Springer, 2016. 405--420. Google Scholar

[8] Park S J, Gazzola M, Park K S. Phototactic guidance of a tissue-engineered soft-robotic ray. Science, 2016, 353: 158-162 CrossRef PubMed ADS Google Scholar

[9] Kelasidi E, Liljeback P, Pettersen K Y. Innovation in Underwater Robots: Biologically Inspired Swimming Snake Robots. IEEE Robot Automat Mag, 2016, 23: 44-62 CrossRef Google Scholar

[10] Zhang A F, Ma S G, Li B, et al. Tracking control of tangential velocity of eel robot based on iterative learning control. Robot, 2018, 40: 769--778. Google Scholar

[11] Wu Z, Yu J, Yuan J. Towards a Gliding Robotic Dolphin: Design, Modeling, and Experiments. IEEE/ASME Trans Mechatron, 2019, 24: 260-270 CrossRef Google Scholar

[12] Sverdrup-Thygeson J, Kelasidi E, Pettersen K Y, et al. The underwater swimming manipulator-a bio-inspired AUV. In: Proceedings of IEEE/OES Autonomous Underwater Vehicles (AUV), Tokyo, 2016. 387--395. Google Scholar

[13] Kelasidi E, Pettersen K Y, Liljebäck P, et al. Locomotion efficiency of underwater snake robots with thrusters. In: Proceedings of IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), Lausanne, 2016. 174--181. Google Scholar

[14] Zhang F, En-Nasr O, Litchman E, et al. Autonomous sampling of water columns using gliding robotic fish: control algorithms and field experiments. In: Proceedings of IEEE International Conference on Robotics and Automation (ICRA), Washington, 2015. 517--522. Google Scholar

[15] Wu Z X, Yu J Z, Yuan J, et al. Mechatronic design and implementation of a novel gliding robotic dolphin. In: Proceedings of IEEE International Conference on Robotics and Biomimetics (ROBIO), Zhuhai, 2015. 267--272. Google Scholar

[16] Noh M M, Arshad M R, Mokhtar R M. Depth and pitch control of USM underwater glider: performance comparison PID vs. LQR. Indian J Geo-Mar Sci, 2011, 40: 200--206. Google Scholar

[17] Tchilian R S, Rafikova E, Gafurov S A. Optimal Control of an Underwater Glider Vehicle. Procedia Eng, 2017, 176: 732-740 CrossRef Google Scholar

[18] Moon J H, Jee S C, Lee H J. Output-feedback control of underwater gliders by buoyancy and pitching moment control: Feedback linearization approach. Int J Control Autom Syst, 2016, 14: 255-262 CrossRef Google Scholar

[19] Sang H, Zhou Y, Sun X. Heading tracking control with an adaptive hybrid control for under actuated underwater glider.. ISA Trans, 2018, 80: 554-563 CrossRef PubMed Google Scholar

[20] Liu J, Wu Z, Yu J. Sliding mode fuzzy control-based path-following control for a dolphin robot. Sci China Inf Sci, 2018, 61: 024201 CrossRef Google Scholar

[21] Zhang Z, Wang F, Guo Y. Multivariable sliding mode backstepping controller design for quadrotor UAV based on disturbance observer. Sci China Inf Sci, 2018, 61: 112207 CrossRef Google Scholar

[22] Pukdeboon C. Extended state observer-based third-order sliding mode finite-time attitude tracking controller for rigid spacecraft. Sci China Inf Sci, 2019, 62: 012206 CrossRef Google Scholar

[23] Gao W B, Hung J C. Variable structure control of nonlinear systems: a new approach. IEEE Trans Ind Electron, 1993, 40: 45-55 CrossRef Google Scholar

[24] Zhang F T, Tan X B. Nonlinear observer design for stabilization of gliding robotic fish. In: Proceedings of American Control Conference, Portland, 2014. 4715--4720. Google Scholar

[25] Yuan J, Wu Z, Yu J. Sliding Mode Observer-Based Heading Control for a Gliding Robotic Dolphin. IEEE Trans Ind Electron, 2017, 64: 6815-6824 CrossRef Google Scholar

[26] Julier S J, Uhlmann J K. Unscented Filtering and Nonlinear Estimation. Proc IEEE, 2004, 92: 401-422 CrossRef Google Scholar

[27] Aghababa M P, Akbari M E. A chattering-free robust adaptive sliding mode controller for synchronization of two different chaotic systems with unknown uncertainties and external disturbances. Appl Math Computation, 2012, 218: 5757-5768 CrossRef Google Scholar

[28] Ioannou P A, Sun J. Robust Adaptive Control. Upper Saddle River: Prentice-Hall, 1996. Google Scholar

[29] Yang H, Ma J. Sliding mode tracking control of an autonomous underwater glider. In: Proceedings of International Conference on Computer Application and System Modeling (ICCASM), Taiyuan, 2010. 555--558. Google Scholar

  • Figure 1

    (Color online) Test of the UGSR in a pool. (a) Gliding; (b) swimming.

  • Figure 2

    (Color online) Modules of the UGSR. (a) Structures of the rotate and telescopic modules; (b) composition of the telescopic module.

  • Figure 3

    (Color online) Representation of coordinate systems in the vertical plane.

  • Figure 4

    (Color online) Diagram of the UKF-based SMC system.

  • Figure 5

    (Color online) Simulation of the SMC system. (a) System inputs $\delta_2$ (top) and $\delta_5$ (bottom); (b) gliding speed $V$ (top) and gliding path angle $\gamma$ (bottom).

  • Figure 6

    (Color online) Simulation of the SMC system under hydrodynamic coefficient disturbances. (a) System inputs $\delta_2$ (top) and $\delta_5$ (bottom); (b) gliding speed $V$ (top) and gliding path angle $\gamma$ (bottom).

  • Figure 7

    (Color online) Simulation of the SMC system under input disturbances. (a) System inputs $\delta_2$ (top) and $\delta_5$ (bottom); (b) gliding speed $V$ (top) and gliding path angle $\gamma$ (bottom).

  • Figure 8

    (Color online) UKF estimation of the SMC system with measurement noise. (a) Filtering result of pitch angle $\theta$; (b) gliding speed $V$ (top) and gliding path angle $\gamma$ (bottom).

  • Figure 9

    (Color online) Simulation of the UKF-based SMC closed-loop system. (a) Control law $\boldsymbol{u}$; (b) system inputs $\delta_2$ and $\delta_5$; (c) sliding surfaces $s_1$ and $s_2$; (d) gliding speed $V$ (top) and gliding path angle $\gamma$ (bottom).

  • Table 1   Hardware and parameters of the developed prototype
    Name Description Parameter Value
    Position servo JRFROPO DS6315HV Length of telescopic module (m) 0.4
    Speed servo Futaba BLS172SV Length of rotate module (m) 0.25
    Hull 7050 aluminum alloy Diameter (m) 0.12
    Seal O-ring, rubber bellow, clamp, thread groove Total length (m) 1.8
    Pressure sensor Bar02 Total mass (kg) 7.9
    Attitude sensor JY901 Elongation range (m) [$-$0.05,~0.05]
  • Table 2   System parameters in the simulation
    Parameter Value Parameter Value
    $M_1$ (kg)20.2 $J_2$ $({\rm~{kg}}\cdot~\rm~{m^2})$5.5118
    $m_h$ (kg) 0.03 $r_h$ (m) 0.025
    $C_D$ $({\rm~{kg}}/\rm~m/rad^2)$ 118.2 $C_{D0}$ $({\rm~{kg}}/\rm~m)$ 3.789
    $C_L$ $({\rm~{kg}}/\rm~m/rad)$ 120.5 $C_{L0}$ $({\rm~{kg}}/\rm~m)$ 0.11
    $C_M$ $({\rm~{kg}/rad})$ $-$13.42 $C_{M0}$ (kg) $-$0.03041
    $C_q$ $({\rm~{kg}\cdot~s/rad})$ $-$2