Adaptive finite-time practical consensus protocols for second-order multiagent systems with nonsymmetric input dead zone and uncertain dynamics

被引:24
|
作者
Liu, Jiehan [1 ]
Wang, Chaoli [1 ]
Li, Xiaobin [2 ]
Cai, Xuan [1 ]
机构
[1] Univ Shanghai Sci & Technol, Dept Control Sci & Engn, Shanghai 200093, Peoples R China
[2] Shanghai Inst Technol, Sch Elect & Elect Engn, Shanghai 201499, Peoples R China
来源
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2019年 / 356卷 / 06期
关键词
NONLINEAR-SYSTEMS; STABILIZATION; FEEDBACK; COMPENSATION; NETWORKS; TRACKING; PLANTS;
D O I
10.1016/j.jfranklin.2019.01.020
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper investigates adaptive finite-time practical consensus protocols for a class of second-order multiagent systems with a positive odd power, nonsymmetric input dead zone and uncertain dynamics under a directed communication topology. In this study, three major steps are employed to address the existence of the positive odd power, nonsymmetric input dead zone and uncertain dynamics. Overall, based on the technique of adding one power integrator, useful preliminary results are obtained by configuring a suitable fraction power. Furthermore, to circumvent input dead-zone nonlinearity, an adaptive fuzzy logic (FL) method is used to estimate the width of the dead zone. Finally, the difficulty in designing finite-time practical consensus protocols for the multiagent systems with uncertain dynamics is handled by using radial basis function neural networks (RBFNNs) to approximate the related unknown nonlinear functions. Then, given some reasonable assumptions, it is shown that finite-time practical consensus of the second-order multiagent systems is obtained by using the proposed distributed control protocols and adaptive laws. In addition, the proper approach for selecting parameters is provided such that the neighborhood position error and parameter estimate errors for each agent converge to predesigned small regions of the origin in a finite time. The effectiveness of the developed algorithm is finally validated through a numerical simulation. (C) 2019 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:3217 / 3244
页数:28
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