Adaptive NN Cooperative Control of Unknown Nonlinear Multiagent Systems With Communication Delays

被引：24
作者：
Psillakis, Haris E. [1 ]
机构：
[1] Natl Tech Univ Athens, Sch Elect & Comp Engn, Athens 15780, Greece
来源：
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | 2021年 / 51卷 / 09期
关键词：
Artificial neural networks; Delays; Adaptive systems; Control systems; Symmetric matrices; Nonlinear systems; Communication time delay; cooperative control; neural networks (NNs); nonlinear multiagent systems (MASs); CONTROL DIRECTIONS; CONSENSUS PROBLEMS; AVERAGE CONSENSUS; OUTPUT REGULATION; AGENTS; NETWORKS; SYNCHRONIZATION;
D O I：
10.1109/TSMC.2019.2950114
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this article, we address the distributed adaptive neural network (NN) control problem for approximate state consensus under communication delays. High-order agent models are considered with unknown nonlinearities and unknown, nonidentical control directions. A novel set of variables called proportional and delayed integral (PdI) consensus error variables are introduced that allow us to recast the approximate consensus problem as an approximate regulation problem. Each PdI variable associated with a certain agent uses only delayed measurements of its neighbors' states in accordance to our delayed communication protocol. Radial basis function (RBF) NNs are employed to approximate the unknown nonlinearities and distributed adaptive NN control laws with Nussbaum gains are proposed that ensure approximate consensus by steering all PdI variables to a neighborhood of zero. Simulation results are also presented that verify the validity of our theoretical analysis.
引用
收藏
页码：5311 / 5321
页数：11
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