二阶多代理系统的固定时间旋转共识控制

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS International Journal of Robust and Nonlinear Control Pub Date : 2024-08-28 DOI:10.1002/rnc.7607
Liwei Kou, Yi Huang, Guangyu Zuo, Long Jian, Yinke Dou
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引用次数: 0

摘要

本文研究了二阶多代理系统在无领导和有领导两种情况下的固定时间旋转共识问题。具体来说,在无领导者情况下,开发了一种分布式控制器,以驱动所有代理在固定时间内达成旋转共识。在领导者跟随的情况下,首先提出一个分布式固定时间观测器来估计旋转领导者的位置。然后,提出一个无需任何速度测量的局部固定时间输出反馈控制器,以实现领导者跟随运动。此外,还应用了积分滑模控制技术来处理多代理系统受到时变外部干扰的情况。基于双极限同质性方法和 Lyapunov 理论,我们证明了所有代理都能在固定时间内达成旋转共识,与初始条件无关。最后,仿真说明了所提控制器的有效性。
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Fixed‐time rotating consensus control of second‐order multi‐agent systems
This article investigates the fixed‐time rotating consensus problem of second‐order multi‐agent systems in both the leaderless and leader‐following cases. Specifically, in the leaderless case, a distributed controller is developed to drive all agents to reach rotating consensus in fixed‐time. In the leader‐following case, a distributed fixed‐time observer is first proposed to estimate the position of a rotating leader. Then, a local fixed‐time output feedback controller without any velocity measurements is proposed to achieve the leader‐following motion. Furthermore, an integral sliding mode control technique is applied to handle the case where the multi‐agent system is subject to time varying external disturbances. Based on the bi‐limit homogeneity method and Lyapunov theory, we prove that all the agents reach the rotating consensus within a fixed time independent of initial conditions. Finally, simulations illustrate the effectiveness of the proposed controllers.
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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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