Distributed average tracking with input saturation

Distributed average tracking with input saturation
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具有输入饱和度的分布式平均跟踪

DOI:
10.1007/s11071-017-3844-z
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发表时间:
2017-10
期刊:
影响因子:
5.6
通讯作者:
Lan Weiyao
Lan Weiyao
中科院分区:
工程技术2区
文献类型:
--
作者:
Liu Hui;Chen Fei;Xiang Linying;Lan Weiyao

文献摘要

参考文献

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本文研究了输入饱和的多智能体系统的分布式平均跟踪问题,其目标是使每个智能体通过局部饱和输入跟踪一组时变参考信号的平均值。本文提出了两种基于低增益反馈和非平滑反馈技术的算法。第一种算法在低增益反馈方案下考虑没有外部输入的参考信号。我们证明了,如果参考文献的系统矩阵是负半定的,则DAT误差最终将是上界。另一种算法考虑具有有界输入的参考信号,其中使用了非光滑反馈的思想。最后,给出了两个仿真算例,验证了理论结果。
In this paper, the distributed average tracking (DAT) problem of a multi-agent system with input saturation is considered, whose objective is to make each agent track the average of a group of time-varying reference signals by local saturated inputs. This paper proposes two algorithms based on the techniques of low-gain feedback and nonsmooth feedback. The first algorithm considers reference signals without external inputs under the low-gain feedback scheme. We show that if the system matrix of the references is negative semi-definite, then the DAT error will be ultimately upper bounded. The other algorithm considers reference signals with bounded inputs, where the idea of nonsmooth feedback is employed. Finally, two simulation examples are presented to validate the theoretical results.
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