Adaptive event-triggered tracking control for a manipulator based on dynamic neural network

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2 Scopus citations

Abstract

This paper is focused on the adaptive event-triggered tracking control of a manipulator subjecting to uncertain dynamics and unknown disturbance. To improve the accuracy of estimation and robustness, the adaptive control scheme based on disturbance observer is developed, in which the uncertain parameters are identified by an echo-state dynamic neural network. Moreover, the event-driven signal transportation mechanism is built in the channel of the controller to the actuator. Both stability and feasibility of the overall system under the proposed control scheme are verified based on Lyapunov theories. Finally, the simulation results demonstrate that our method could accomplish both motion tracking in a robust way, meanwhile could reduce communication.

Original languageEnglish
Title of host publication2021 6th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages412-417
Number of pages6
ISBN (Electronic)9780738133645
DOIs
StatePublished - 3 Jul 2021
Externally publishedYes
Event6th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2021 - Chongqing, China
Duration: 3 Jul 20215 Jul 2021

Publication series

Name2021 6th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2021

Conference

Conference6th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2021
Country/TerritoryChina
CityChongqing
Period3/07/215/07/21

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