Neuro-adaptive cooperative control for high-order nonlinear multi-agent systems with uncertainties

IF 1.6 4区计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS

International Journal of Applied Mathematics and Computer Science Pub Date : 2021-12-01 DOI:10.34768/amcs-2021-0044

Cheng Peng, Anguo Zhang, Junyu Li

引用次数: 3

Abstract

Abstract The consensus problem for a class of high-order nonlinear multi-agent systems (MASs) with external disturbance and system uncertainty is studied. We design an online-update radial basis function (RBF) neural network based distributed adaptive control protocol, where the sliding model control method is also applied to eliminate the influence of the external disturbance and system uncertainty. System consensus is verified by using the Lyapunov stability theorem, and sufficient conditions for cooperative uniform ultimately boundedness (CUUB) are also derived. Two simulation examples demonstrate the effectiveness of the proposed method for both homogeneous and heterogeneous MASs.

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高阶非线性不确定多智能体系统的神经自适应协同控制

研究了一类具有外部干扰和系统不确定性的高阶非线性多智能体系统的一致性问题。设计了一种基于在线更新径向基函数(RBF)神经网络的分布式自适应控制协议，并采用滑模控制方法消除了外部干扰和系统不确定性的影响。利用Lyapunov稳定性定理验证了系统的一致性，并给出了系统一致最终有界性的充分条件。两个仿真实例验证了该方法对均质和非均质质量的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Applied Mathematics and Computer Science 工程技术-计算机：人工智能

CiteScore

4.10

自引率

21.10%

发文量

审稿时长

4.2 months

期刊介绍： The International Journal of Applied Mathematics and Computer Science is a quarterly published in Poland since 1991 by the University of Zielona Góra in partnership with De Gruyter Poland (Sciendo) and Lubuskie Scientific Society, under the auspices of the Committee on Automatic Control and Robotics of the Polish Academy of Sciences. The journal strives to meet the demand for the presentation of interdisciplinary research in various fields related to control theory, applied mathematics, scientific computing and computer science. In particular, it publishes high quality original research results in the following areas: -modern control theory and practice- artificial intelligence methods and their applications- applied mathematics and mathematical optimisation techniques- mathematical methods in engineering, computer science, and biology.