Data-Driven Multiagent Systems Consensus Tracking Using Model Free Adaptive Control

被引：246

作者：

Bu, Xuhui ^{[1
]}

Hou, Zhongsheng ^{[2
]}

Zhang, Hongwei ^{[1
]}

机构：

[1] Henan Polytech Univ, Sch Elect Engn & Automat, Jiaozuo 454003, Peoples R China

[2] Beijing Jiaotong Univ, Sch Elect & Informat Engn, Adv Control Syst Lab, Beijing 100044, Peoples R China

来源：

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS | 2018年 / 29卷 / 05期

基金：

中国国家自然科学基金;

关键词：

Consensus tracking; data-driven design; model free adaptive control (MFAC); multiagent systems; ITERATIVE LEARNING CONTROL; ALGORITHMS; NETWORKS;

D O I：

10.1109/TNNLS.2017.2673020

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper investigates the data-driven consensus tracking problem for multiagent systems with both fixed communication topology and switching topology by utilizing a distributed model free adaptive control (MFAC) method. Here, agent's dynamics are described by unknown nonlinear systems and only a subset of followers can access the desired trajectory. The dynamical linearization technique is applied to each agent based on the pseudo partial derivative, and then, a distributed MFAC algorithm is proposed to ensure that all agents can track the desired trajectory. It is shown that the consensus error can be reduced for both time invariable and time varying desired trajectories. The main feature of this design is that consensus tracking can be achieved using only input-output data of each agent. The effectiveness of the proposed design is verified by simulation examples.

引用

页码：1514 / 1524

页数：11

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