Neural network adaptive control of teleoperation systems with uncertainties and time-varying delay

Kebria, Parham M, Khosravi, Abbas, Nahavandi, Saeid, Najdovski, Zoran and Hilton, Stephen John 2018, Neural network adaptive control of teleoperation systems with uncertainties and time-varying delay, in CASE 2018 : Proceedings of the 2018 IEEE 14th International Conference on Automation Science and Engineering, Institute of Electrical and Electronics Engineers, Piscataway, N.J., pp. 252-257, doi: 10.1109/COASE.2018.8560394.

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Title Neural network adaptive control of teleoperation systems with uncertainties and time-varying delay
Author(s) Kebria, Parham M
Khosravi, AbbasORCID iD for Khosravi, Abbas orcid.org/0000-0001-6927-0744
Nahavandi, SaeidORCID iD for Nahavandi, Saeid orcid.org/0000-0002-0360-5270
Najdovski, ZoranORCID iD for Najdovski, Zoran orcid.org/0000-0002-8880-8287
Hilton, Stephen John
Conference name IEEE Robotics and Automation Society. Conference (14th : 2018 : Munich, Germany)
Conference location Munich, Germany
Conference dates 2018/08/20 - 2018/08/24
Title of proceedings CASE 2018 : Proceedings of the 2018 IEEE 14th International Conference on Automation Science and Engineering
Editor(s) [Unknown]
Publication date 2018
Series IEEE Robotics and Automation Society Conference
Start page 252
End page 257
Total pages 6
Publisher Institute of Electrical and Electronics Engineers
Place of publication Piscataway, N.J.
Keyword(s) Teleoperation systems
Neural networks
Adaptive control
Model uncertainties
Time-delays
Science & Technology
Technology
Automation & Control Systems
Engineering, Electrical & Electronic
Engineering
Summary This paper studies the model uncertainties of Internet-based bilateral teleoperation systems under asymmetric time-varying delays. Generally, master and slave subsystems of a teleoperation process are robots with complex dynamics. This complexity makes the modelling process difficult, and usually with unavoidable uncertainties. Along with the latency through the communication network between the master and slave systems, the control problem becomes critical in terms of maintaining stability and performance of the system. Describing the modelling procedure and properties, this paper proposes an adaptive control scheme strengthened with a radial basis function (RBF) neural network (NN)-based algorithm to cope with the model uncertainties and also for stabilisation in the presence of time-varying delays. Using Lyapunov theorem, the stability analysis of the overall system under the proposed control method is investigated. Furthermore, simulation and experimental studies show the effectiveness and performance of this control for a teleoperation system.
ISBN 9781538635933
ISSN 2161-8070
2161-8089
Language eng
DOI 10.1109/COASE.2018.8560394
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2018, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30123291

Document type: Conference Paper
Collections: Centre for Intelligent Systems Research
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