In this article, a leader–follower asymptotic consensus control strategy is developed for a class of linear multiagent systems (MASs) with unknown external disturbances and measurement noises. First, the preconditions, the minimum phase condition (MPC) and observer matching condition (OMC), are discussed in detail, and an equivalent result under these two preconditions is given. In this way, the corresponding results from Corless and Tu (1998) are improved. Meanwhile, a reduced-order observer is designed for a constructed augmented system to estimate the system states and noises of each agent. Next, with the help of a traditional interval observer, a novel unknown disturbance reconstruction method is developed, and the reconstruction can converge to the unknown disturbance asymptotically and decouple from the control input. The subsequent asymptotic consensus is accomplished by utilizing an observer-based control scheme, with its design satisfying the so-called separation principle. Finally, two simulation examples are given to verify the effectiveness and show the advantages of the proposed methods.

中文翻译：

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多智能体系统的主从渐近一致性控制：一种基于观察者的扰动重建方法


在本文中，为一类具有未知外部干扰和测量噪声的线性多智能体系统（MAS）开发了一种领导者-跟随者渐近一致控制策略。首先，详细讨论了前提条件，即最小相位条件（MPC）和观测器匹配条件（OMC），并给出了这两个前提条件下的等效结果。这样，Corless和Tu(1998)的相应结果得到了改进。同时，为构建的增强系统设计了降阶观测器来估计每个智能体的系统状态和噪声。接下来，借助传统的区间观测器，提出了一种新颖的未知扰动重构方法，该重构可以渐近收敛于未知扰动并与控制输入解耦。随后的渐近共识是通过利用基于观察者的控制方案来实现的，其设计满足所谓的分离原理。最后给出两个仿真例子来验证所提方法的有效性和优势。