File(s) under permanent embargo
Type-2 fuzzy neural network synchronization of teleoperation systems with delay and uncertainties
conference contribution
posted on 2019-01-01, 00:00 authored by P M Kebria, Abbas KhosraviAbbas Khosravi, Seyed Mohammad Jafar Jalali, Saeid Nahavandi© 2019 IEEE. This paper concerns the problem of uncertainties and time-delays in teleoperation systems. Human operators at the master side and partially unknown environments in the remote workspace introduces extreme uncertainties to the teleoperation process. Outstanding capability of type-2 fuzzy methodologies in dealing with uncertainties motivated us to apply this method in the design of a controller for teleoperation systems. Moreover, employing artificial neural networks, we propose an online learning approach that adaptively tunes the type-2 fuzzy-based control strategy. Asymptotic convergence of the learning methodology, and subsequently, the stability of the system is verified by Lyapunov-Krasovskii approach. Furthermore, experimental evaluations justify the performance of the developed control scheme.
History
Event
Automation Science and Engineering. Conference (15th : 2019 : Vancouver, B.C.)Volume
2019-AugustPagination
1625 - 1630Publisher
IEEELocation
Vancouver, B.C.Place of publication
Piscataway, N.J.Publisher DOI
Start date
2019-08-22End date
2019-08-26ISSN
2161-8070eISSN
2161-8089ISBN-13
9781728103556Language
engPublication classification
E1 Full written paper - refereedTitle of proceedings
CASE 2019 : IEEE 15th International Conference on Automation Science and Engineering (CASE) : August 22-26, 2019, Vancouver, BC, CanadaUsage metrics
Categories
No categories selectedKeywords
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC