Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/134017
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Type: Journal article
Title: Robust and Collision-Free Formation Control of Multi-Agent Systems with Limited Information
Author: Fei, Y.
Shi, P.
Lim, C.C.
Citation: IEEE Transactions on Neural Networks and Learning Systems, 2023; 34(8):4286-4295
Publisher: Institute of Electrical and Electronics Engineers
Issue Date: 2023
ISSN: 1045-9227
2162-2388
Statement of
Responsibility: 
Yang Fei, Peng Shi, and Cheng-Chew Lim
Abstract: This article investigates the collision-free cooperative formation control problem for second-order multiagent systems with unknown velocity, dynamics uncertainties, and limited reference information. An observer-based sliding mode control law is proposed to ensure both the convergence of the system’s tracking error and the boundedness of the relative distance between each pair of agents. First, two new finite-time neural-based observer designs are introduced to estimate both the agent velocity and the system uncertainty. The sliding mode differentiator is then employed for every agent to approximate the unknown derivatives of the formation reference to further construct the limited-information-based sliding mode controller. To ensure that the system is collision-free, artificial potential fields are introduced along with a time-varying topology. An example of a multiple omnidirectional robot system is used to conduct numerical simulations, and necessary comparisons are made to justify the effectiveness of the proposed limited information-based control scheme.
Keywords: Collision avoidance; formation control; multiagent systems; neural-based observer; sliding mode control
Description: Published 8 August 2023
Rights: © 2021 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://www.ieee.org/publications/rights/index.html for more information.
DOI: 10.1109/TNNLS.2021.3112679
Grant ID: http://purl.org/au-research/grants/arc/DP170102644
Published version: http://dx.doi.org/10.1109/tnnls.2021.3112679
Appears in Collections:Electrical and Electronic Engineering publications

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