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不确定非线性严格反馈多智能体系统的保连通性一致性跟踪:一种误差变换方法

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

作者信息

Yoo Sung Jin

出版信息

IEEE Trans Neural Netw Learn Syst. 2018 Sep;29(9):4542-4548. doi: 10.1109/TNNLS.2017.2764495. Epub 2017 Nov 9.

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.

摘要

本文解决了具有有限通信范围的不确定非线性严格反馈多智能体系统的分布式保持连通性的自适应一致性跟踪问题。与现有的不确定非线性下三角多智能体系统的一致性结果相比,本文的主要贡献在于提出了一种基于误差变换的设计方法,以在一致性跟踪领域中保持初始连通模式,即针对不确定非线性下三角多智能体系统同时考虑连通性保持和一致性跟踪问题。基于非线性变换误差和神经网络函数逼近器建立了动态表面设计,以构造每个跟随者的局部控制器。此外,还推导了一个技术引理,用于在李雅普诺夫意义下分析所提出的保持连通性的一致性方案的稳定性。

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