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Connectivity-Preserving Consensus Tracking of Uncertain Nonlinear Strict-Feedback Multiagent Systems: An Error Transformation Approach

Authors
Yoo, Sung Jin
Issue Date
Sep-2018
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
Adaptive consensus tracking; connectivity preservation; error transformation; function approximation technique; networked nonlinear systems
Citation
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, v.29, no.9, pp 4542 - 4548
Pages
7
Journal Title
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
Volume
29
Number
9
Start Page
4542
End Page
4548
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/819
DOI
10.1109/TNNLS.2017.2764495
ISSN
2162-237X
2162-2388
Abstract
This brief addresses a distributed connectivity-preserving adaptive consensus tracking problem of uncertain nonlinear strict-feedback multiagent systems with limited communication ranges. Compared with existing consensus results for uncertain nonlinear lower triangular multiagent systems, the main contribution of this brief is to present an error-transformation-based design methodology to preserve initial connectivity patterns in the consensus tracking field, namely, both connectivity preservation and consensus tracking problems are considered for uncertain nonlinear lower triangular multiagent systems. A dynamic surface design based on nonlinearly transformed errors and neural network function approximators is established to construct the local controller of each follower. In addition, a technical lemma is derived to analyze the stability of the proposed connectivity-preserving consensus scheme in the Lyapunov sense.
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Yoo, Sung Jin
창의ICT공과대학 (전자전기공학부)
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