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Research Papers

Bilateral Control and Stabilization of Asymmetric Teleoperators With Bounded Time-Varying Delays

[+] Author and Article Information
Trent Hilliard

Department of Mechanical Engineering,
Dalhousie University,
P.O. Box 15000,
Halifax, NS B3H 4R2, Canada
e-mail: Trent.Hilliard@Dal.Ca

Ya-Jun Pan

Associate Professor
Mem. ASME
Department of Mechanical Engineering,
Dalhousie University,
P.O. Box 15000,
Halifax, NS B3H 4R2, Canada
e-mail: Yajun.Pan@Dal.Ca

See the following two links for more information on the devices: http://www.sensable.com/haptic-phantom-omni.htm and http://www.novint.com/index.php/novintfalcon.

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received May 12, 2013; final manuscript received February 26, 2014; published online May 12, 2014. Assoc. Editor: Qingze Zou.

J. Dyn. Sys., Meas., Control 136(5), 051001 (May 12, 2014) (12 pages) Paper No: DS-13-1196; doi: 10.1115/1.4026967 History: Received May 12, 2013; Revised February 26, 2014

A novel control scheme for asymmetric bilateral teleoperation systems is developed based on linear models of the hardware, with considerations in the existence of communication time delays. The master and slave manipulators were modeled as linear single degree of freedom systems. The human user force was modeled based on the band limited availability of human motion, and the environmental force was modeled as a spring and damper combination based on the slave position. The configuration of the whole system represents a relatively general framework for the teleoperation systems. The main contribution of the work can be concluded as follows. First to deal with asymmetric systems in teleoperation, an impedance matching approach was applied to the master side dynamics, while a static error feedback gain was used to stabilize the slave side dynamics. Second, in the existence of bounded random time-varying delays, approaches and techniques based on the Lyapunov method proposed for network controlled systems are now proposed for bilateral teleoperation systems. Specifically, a Lyapunov functional is proposed with consideration for the upper and lower bound of random delays. Linear matrix inequality (LMI) techniques are used with rigorous stability proof to design the slave side controller control gains. Furthermore, the cone complementarity algorithm is used to deal with nonlinear terms within the LMI under the new formulation. Finally, the applications of the proposed algorithm to haptic devices are described thoroughly, and experimental results with comparisons to simulation results are demonstrated to show the effectiveness of the proposed approach.

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Figures

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Fig. 1

Unilateral teleoperation system layout

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Fig. 2

Bilateral teleoperation system layout [10]

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Fig. 3

Diagram of forces and their assumed directions on 1-DOF manipulators

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Fig. 4

Error as γ1 and γ2 varies

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Fig. 5

Positional error and its maximum bound under a sinusoidal input with lower delay bound τ1 and upper delay bound τ2

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Fig. 6

(a) Phantom Omni haptic device and (b) Novint Falcon haptic device

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Fig. 7

Experimental forces without contact (a) external force, (b) control signal, and (c) net force

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Fig. 8

Experimental states without contact (a) position, (b) velocity, and (c) positional error xs-xm

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Fig. 9

Simulation forces without contact (a) external force, (b) control signal, and (c) net force

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Fig. 10

Simulation states without contact (a) position, (b) velocity, and (c) positional error

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Fig. 11

Experimental forces with direct foam contact under sinusoid input (a) external force, (b) control signal, and (c) net force

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Fig. 12

Direct foam contact

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Fig. 13

Experimental states with direct foam contact under sinusoid input (a) position, (b) velocity, and (c) positional error

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Fig. 14

Contact with plastic affixed to the foam

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Fig. 15

Experimental forces with contact under sinusoid input (a) external force, (b) control signal, and (c) net force

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Fig. 16

Experimental states with contact under sinusoid input (a) position, (b) velocity, and (c) positional error

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Fig. 17

Simulation forces with contact under sinusoid input (a) external force, (b) control signal, and (c) net force

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Fig. 18

Simulation states with contact under sinusoid input (a) position, (b) velocity, and (c) positional error

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Fig. 19

Experimental forces with contact under modified step input (a) external force, (b) control signal, and (c) net force

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Fig. 20

Experimental states with contact under modified step input (a) position, (b) velocity, and (c) positional error

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Fig. 21

Simulation forces with contact under modified step input (a) external force, (b) control signal, and (c) net force

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Fig. 22

Simulation states with contact under modified step input (a) position, (b) velocity, and (c) positional error

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Fig. 23

Simulation results on the performance using wave variable approach with contact under sinusoid input (a) positions, (b) velocity, and (c) position error

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Fig. 24

Experimental results on the performance using wave variable approach with contact under faster sinusoid input with higher magnitude (a) positions, (b) velocity, and (c) control forces

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