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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

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

Abstract

With its strong endurance and high maneuverability, an underwater gliding snake-like robot (UGSR) is a strong potential candidate for aquatic exploration and monitoring. The major feature of the UGSR, which distinguishes it from other snake-like robots, is long range and long operation duration by gliding. This study establishes a gliding motion control system for the UGSR based on a sliding mode controller (SMC). The control system stabilizes the system and suppresses the uncertainties and unknown disturbances. In this strategy, chattering is reduced based on the reaching law method. To circumvent the difficulty of velocity measurements, a nonlinear observer based on an unscented Kalman filter (UKF) is employed for state estimation and random noise handling. The effectiveness of the proposed controller and observer is verified by simulating the UKF-based SMC closed-loop system.


Acknowledgment

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


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  • 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

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