To perform complicated tasks in the unstructured environment, teleoperation robot systems integrating human operators in the control loop have been investigated by researchers recently. Currently, most of the existing researches on the teleoperation robot systems focus on stability-guaranteed issues in the presence of time delays existing in the communication channel between the master and slave site. However, the high accurate performance-oriented motion tracking in the slave site is still a challenging issue due to the following facts: with the coupling dynamics existing in the joints, the dynamics of the slave robot behaves complexly significantly when the degree of freedoms (DoFs) increase, which makes the model compensation extremely difficult in the controller design. Next, parameters variations such as payload changes and effects of modeling errors exist in the actual dynamics of the slave robot manipulator. In this paper, to achieve a high accurate motion tracking performance in the slave site, a teleoperation robot system is configured in which the slave robot is a Baxter manipulator with 7 DoFs. The complicated dynamic model of the Baxter manipulator with 7 DoFs is first established and then further formulated in a linear parametric form for the purpose of online parameter adaptations. In this way, an adaptive robust control (ARC) strategy is developed to deal with the payload variations and modelling errors effectively. The simulation results on the configured teleoperation robot systems indicate that a higher accurate motion tracking performance can be achieved by the developed ARC controller in the presence of payload variations and modelling uncertainties in the Baxter manipulator with 7 DoFs.
- Dynamic Systems and Control Division
Adaptive Robust Control of a 7-DoFs Teleoperation Robot System With Payload Variations and Disturbances
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Hu, J, Chen, Z, Yuan, M, & Yao, B. "Adaptive Robust Control of a 7-DoFs Teleoperation Robot System With Payload Variations and Disturbances." Proceedings of the ASME 2018 Dynamic Systems and Control Conference. Volume 1: Advances in Control Design Methods; Advances in Nonlinear Control; Advances in Robotics; Assistive and Rehabilitation Robotics; Automotive Dynamics and Emerging Powertrain Technologies; Automotive Systems; Bio Engineering Applications; Bio-Mechatronics and Physical Human Robot Interaction; Biomedical and Neural Systems; Biomedical and Neural Systems Modeling, Diagnostics, and Healthcare. Atlanta, Georgia, USA. September 30–October 3, 2018. V001T03A004. ASME. https://doi.org/10.1115/DSCC2018-9168
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