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Teleoperation Control Based on Combination of Wave Variable and Neural Networks

Chenguang Yang, Xingjian Wang, Zhijun Li, Yanan Li, Chun-Yi Su

IEEE Transactions on Systems, Man, and Cybernetics: Systems, Volume: 47, Issue: 8, Pages: 2125 - 2136

Swansea University Author: Chenguang Yang

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DOI (Published version): 10.1109/TSMC.2016.2615061

Abstract

In this paper, a novel control scheme is developed for a teleoperation system, combining the radial basis function (RBF) neural networks (NNs) and wave variable technique to simultaneously compensate for the effects caused by communication delays and dynamics uncertainties. The teleoperation system...

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Published in: IEEE Transactions on Systems, Man, and Cybernetics: Systems
ISSN: 2168-2216 2168-2232
Published: 2017
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URI: https://cronfa.swan.ac.uk/Record/cronfa39979
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spelling 2018-08-06T09:55:11.2016246 v2 39979 2018-05-06 Teleoperation Control Based on Combination of Wave Variable and Neural Networks d2a5024448bfac00a9b3890a8404380b Chenguang Yang Chenguang Yang true false 2018-05-06 EEN In this paper, a novel control scheme is developed for a teleoperation system, combining the radial basis function (RBF) neural networks (NNs) and wave variable technique to simultaneously compensate for the effects caused by communication delays and dynamics uncertainties. The teleoperation system is set up with a TouchX joystick as the master device and a simulated Baxter robot arm as the slave robot. The haptic feedback is provided to the human operator to sense the interaction force between the slave robot and the environment when manipulating the stylus of the joystick. To utilize the workspace of the telerobot as much as possible, a matching process is carried out between the master and the slave based on their kinematics models. The closed loop inverse kinematics (CLIK) method and RBF NN approximation technique are seamlessly integrated in the control design. To overcome the potential instability problem in the presence of delayed communication channels, wave variables and their corrections are effectively embedded into the control system, and Lyapunov-based analysis is performed to theoretically establish the closed-loop stability. Comparative experiments have been conducted for a trajectory tracking task, under the different conditions of various communication delays. Experimental results show that in terms of tracking performance and force reflection, the proposed control approach shows superior performance over the conventional methods. Journal Article IEEE Transactions on Systems, Man, and Cybernetics: Systems 47 8 2125 2136 2168-2216 2168-2232 17 7 2017 2017-07-17 10.1109/TSMC.2016.2615061 COLLEGE NANME Engineering COLLEGE CODE EEN Swansea University 2018-08-06T09:55:11.2016246 2018-05-06T12:18:43.2352710 Faculty of Science and Engineering School of Engineering and Applied Sciences - Uncategorised Chenguang Yang 1 Xingjian Wang 2 Zhijun Li 3 Yanan Li 4 Chun-Yi Su 5 0039979-06052018122624.pdf SMCA_final.pdf 2018-05-06T12:26:24.6230000 Output 5597154 application/pdf Accepted Manuscript true 2018-05-06T00:00:00.0000000 true eng
title Teleoperation Control Based on Combination of Wave Variable and Neural Networks
spellingShingle Teleoperation Control Based on Combination of Wave Variable and Neural Networks
Chenguang Yang
title_short Teleoperation Control Based on Combination of Wave Variable and Neural Networks
title_full Teleoperation Control Based on Combination of Wave Variable and Neural Networks
title_fullStr Teleoperation Control Based on Combination of Wave Variable and Neural Networks
title_full_unstemmed Teleoperation Control Based on Combination of Wave Variable and Neural Networks
title_sort Teleoperation Control Based on Combination of Wave Variable and Neural Networks
author_id_str_mv d2a5024448bfac00a9b3890a8404380b
author_id_fullname_str_mv d2a5024448bfac00a9b3890a8404380b_***_Chenguang Yang
author Chenguang Yang
author2 Chenguang Yang
Xingjian Wang
Zhijun Li
Yanan Li
Chun-Yi Su
format Journal article
container_title IEEE Transactions on Systems, Man, and Cybernetics: Systems
container_volume 47
container_issue 8
container_start_page 2125
publishDate 2017
institution Swansea University
issn 2168-2216
2168-2232
doi_str_mv 10.1109/TSMC.2016.2615061
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Uncategorised{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Uncategorised
document_store_str 1
active_str 0
description In this paper, a novel control scheme is developed for a teleoperation system, combining the radial basis function (RBF) neural networks (NNs) and wave variable technique to simultaneously compensate for the effects caused by communication delays and dynamics uncertainties. The teleoperation system is set up with a TouchX joystick as the master device and a simulated Baxter robot arm as the slave robot. The haptic feedback is provided to the human operator to sense the interaction force between the slave robot and the environment when manipulating the stylus of the joystick. To utilize the workspace of the telerobot as much as possible, a matching process is carried out between the master and the slave based on their kinematics models. The closed loop inverse kinematics (CLIK) method and RBF NN approximation technique are seamlessly integrated in the control design. To overcome the potential instability problem in the presence of delayed communication channels, wave variables and their corrections are effectively embedded into the control system, and Lyapunov-based analysis is performed to theoretically establish the closed-loop stability. Comparative experiments have been conducted for a trajectory tracking task, under the different conditions of various communication delays. Experimental results show that in terms of tracking performance and force reflection, the proposed control approach shows superior performance over the conventional methods.
published_date 2017-07-17T03:50:50Z
_version_ 1763752490645323776
score 11.013037

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