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Research Papers

Bilateral Adaptive Control of Nonlinear Teleoperation Systems With Uncertain Dynamics and Dead-Zone

[+] Author and Article Information
Xia Liu

School of Electrical Engineering
and Electronic Information,
Xihua University,
Chengdu 610039, Sichuan, China
e-mail: xliu_uestc@yahoo.com

Mahdi Tavakoli

Department of Electrical and Computer
Engineering,
University of Alberta,
Edmonton, AB T6G 2V4, Canada
e-mail: mahdi.tavakoli@ualberta.ca

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT,AND CONTROL. Manuscript received February 18, 2016; final manuscript received June 24, 2018; published online July 23, 2018. Editor: Joseph Beaman.

J. Dyn. Sys., Meas., Control 140(12), 121004 (Jul 23, 2018) (10 pages) Paper No: DS-16-1109; doi: 10.1115/1.4040666 History: Received February 18, 2016; Revised June 24, 2018

Dead-zone is one of the most common hard nonlinearities ubiquitous in master–slave teleoperation systems, particularly in the slave robot joints. However, adaptive control techniques applied in teleoperation systems usually deal with dynamic uncertainty but ignore the presence of dead-zone. Dead-zone has the potential to remarkably deteriorate the transparency of a teleoperation system in the sense of position and force tracking performance or even destabilizing the system if not compensated for in the control scheme. In this paper, an adaptive bilateral control scheme is proposed for nonlinear teleoperation systems in the presence of both uncertain dynamics and dead-zone. An adaptive controller is designed for the master robot with dynamic uncertainties and the other is developed for the slave robot with both dynamic uncertainties and unknown dead-zone. The two controllers are incorporated into the four-channel bilateral teleoperation control framework to achieve transparency. The transparency and stability of the closed-loop teleoperation system is studied via a Lyapunov function analysis. Comparisons with the conventional adaptive control which merely deal with dynamic uncertainties in the simulations demonstrate the validity of the proposed approach.

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References

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Figures

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Fig. 1

Dead-zone at the input of the slave robot

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Fig. 2

Architecture of the proposed four-channel adaptive teleoperation control

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Fig. 8

Positions for the proposed adaptive control with measurement noise: (a) position of joint 1 and (b) position of joint 2

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Fig. 9

Torques for the conventional adaptive control with measurement noise: (a) torque of joint 1 and (b) torque of joint 2

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Fig. 10

Torques for the proposed adaptive control with measurement noise: (a) torque of joint 1 and (b) torque of joint 2

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Fig. 3

Positions and position errors for the conventional adaptive control: (a) position of joint 1, (b) position of joint 2, (c) position error of joint 1, and (d) position error of joint 2

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Fig. 4

Positions and position errors for the proposed adaptive control: (a) position of joint 1, (b) position of joint 2, (c) position error of joint 1, and (d) position error of joint 2

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Fig. 5

Torques and torque errors for the conventional adaptive control: (a) torque of joint 1, (b) torque of joint 2, (c) torque error of joint 1, and (d) torque error of joint 2

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Fig. 6

Torques and torque errors for the proposed adaptive control: (a) torque of joint 1, (b) torque of joint 2, (c) torque error of joint 1, and (d) torque error of joint 2

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Fig. 7

Positions for the conventional adaptive control with measurement noise: (a) position of joint 1 and (b) position of joint 2

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