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

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46
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51

초록

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.

키워드

Adaptive consensus tracking; connectivity preservation; error transformation; function approximation technique; networked nonlinear systems; ADAPTIVE NEURAL-CONTROL; DEAD-ZONE INPUT; COORDINATION CONTROL; DIRECTED NETWORKS; AGENTS; SYNCHRONIZATION; TOPOLOGIES; FORM
제목
Connectivity-Preserving Consensus Tracking of Uncertain Nonlinear Strict-Feedback Multiagent Systems: An Error Transformation Approach
저자
Yoo, Sung Jin
DOI
10.1109/TNNLS.2017.2764495
발행일
2018-09
유형
Article
저널명
IEEE Transactions on Neural Networks and Learning Systems
권
29
호
9
페이지
4542 ~ 4548