Fixed-Time Control Lyapunov Function for Networked Non-Linear Uncertain Systems

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Yi Dong, Zhiyong Chen
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引用次数: 0

Abstract

This paper introduces a novel tool based on Lyapunov functions, aimed at analyzing the fixed-time property of networked non-linear uncertain systems while incorporating a specifically designed control law. The applicability of this tool is demonstrated by addressing the fixed-time synchronization challenge within non-linear uncertain multi-agent systems (MASs) operating in a leader-following scenario. In this scenario, the desired trajectory stems from a general non-linear system, and a two-part solution is presented. Both segments of the solution leverage the innovative Lyapunov function-based tool. The first component entails a fixed-time non-linear state feedback observer, engineered to estimate the leader system's state within a directed communication network. The second component offers a fixed-time control law, designed to regulate the trajectories of the agents. This paper explores two categories of non-linear agents with first-order and second-order dynamics, taking into account parametric uncertainties.

Abstract Image

网络非线性不确定系统的定时控制Lyapunov函数
本文介绍了一种基于李雅普诺夫函数的新工具,旨在分析网络非线性不确定系统的定时特性,同时结合专门设计的控制律。通过解决在领导者跟随场景中运行的非线性不确定多智能体系统(MASs)中的固定时间同步挑战,证明了该工具的适用性。在这种情况下,期望的轨迹源于一般的非线性系统,并提出了两部分的解决方案。解决方案的两个部分都利用了创新的基于Lyapunov函数的工具。第一个组件需要一个固定时间非线性状态反馈观测器,用于估计有向通信网络中的领导系统的状态。第二部分提供了一个固定时间的控制律,用来调节agent的运动轨迹。本文研究了考虑参数不确定性的两类一阶和二阶动力学非线性智能体。
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 Robust and Nonlinear Control
International Journal of Robust and Nonlinear Control 工程技术-工程:电子与电气
CiteScore
6.70
自引率
20.50%
发文量
505
审稿时长
2.7 months
期刊介绍: Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.
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