Affine Formation Obstacle Avoidance Control for Multi-Agent Systems Under an Improved Disturbance Observer

IF 3.2 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

International Journal of Robust and Nonlinear Control Pub Date : 2026-04-03 Epub Date: 2026-01-19 DOI:10.1002/rnc.70398

Wen Qin, Mouquan Shen, Hamid Reza Karimi, Zheng Hong Zhu

引用次数: 0

Abstract

The paper addresses affine formation obstacle avoidance control of multi-agent systems (MASs) with unknown external disturbances. An improved disturbance observer is developed to enhance the estimation accuracy. An affine transformation and an adaptive controller are exploited to dynamically adjust formation against unknown obstructed environments. Sufficient criteria are established to achieve obstacle avoidance with zero velocity, constant velocity, and time-varying velocity, respectively. Finally, two examples are simulated to deliver the effectiveness of the proposed control schemes.

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改进扰动观测器下多智能体系统仿射编队避障控制

研究了具有未知外部干扰的多智能体系统的仿射编队避障控制问题。为了提高估计精度，提出了一种改进的扰动观测器。利用仿射变换和自适应控制器对未知障碍物环境进行动态调整。分别建立了零速度、匀速和时变速度的避障准则。最后，通过仿真验证了所提控制方案的有效性。

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 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.