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Type: Conference paper
Title: Adaptive neural network consensus control of multi-robot systems with output constraints
Author: Sun, Y.
Shi, P.
Lim, C.C.
Citation: Proceedings of the IEEE International Conference on Intelligence and Safety for Robotics (ISR 2021), 2021, pp.288-291
Publisher: IEEE
Publisher Place: online
Issue Date: 2021
ISBN: 9781665438629
Conference Name: IEEE International Conference on Intelligence and Safety for Robotics (ISR) (4 Mar 2021 - 6 Mar 2021 : virtual online)
Statement of
Yuan Sun, Peng Shi and Cheng-Chew Lim
Abstract: Addressing the leader-follower consensus control problem with time-varying output constraints for a class of second-order nonlinear multi-robot systems, we apply a unified barrier Lyapunov function to transform the constrained output state into the unconstrained one, while removing the feasibility condition existing in the traditional barrier Lyapunov function. Using the radial basis function-based neural network to approximate the unknown nonlinear function, we derive an adaptive neural network consensus controller to ensure that each robot follows the predefined trajectory of a leader. We then verify the effectiveness of the consensus control via simulation studies on a team of robotic manipulators.
Rights: ©2021 IEEE
DOI: 10.1109/ISR50024.2021.9419548
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Appears in Collections:Aurora harvest 8
Electrical and Electronic Engineering publications

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