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农业采摘多机器人系统采样控制的分布式平均问题

Distributed Averaging Problems of Agriculture Picking Multi-Robot Systems Sampled Control.

作者信息

Ma Fengying, Yao Hui, Du Mingjun, Ji Peng, Si Xiaoan

机构信息

School of Information and Automation Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China.

出版信息

Front Plant Sci. 2022 Jul 14;13:898183. doi: 10.3389/fpls.2022.898183. eCollection 2022.

DOI:10.3389/fpls.2022.898183
PMID:35909779
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9331186/
Abstract

Distributed control of agriculture picking multi-robot systems has been widely used in the field of smart agriculture, this paper aims to explore the distributed averaging problems of agriculture picking multi-robot systems under directed communication topologies by taking advantage of the sampled data. With the algebraic graph theory concepts and the matrix theory, a distributed protocol is proposed based on the nearest sampled neighbor information. It is shown that under the proposed protocol, the states of all agents can be guaranteed to reach average consensus whose value is the averaging of the initial states of all agents. Besides, when considering time-delay, the other distributed protocol is constructed, in which a time margin of the time-delay can be determined simultaneously. The necessary and sufficient consensus results can be developed even though the time delay exists. Simulation results are given to demonstrate the effectiveness of our developed consensus results.

摘要

分布式农业采摘多机器人系统控制在智慧农业领域已得到广泛应用,本文旨在利用采样数据探讨有向通信拓扑下农业采摘多机器人系统的分布式平均问题。借助代数图论概念和矩阵理论,基于最近采样邻居信息提出了一种分布式协议。结果表明,在所提协议下,所有智能体的状态能够保证达到平均一致性,其值为所有智能体初始状态的平均值。此外,在考虑时延的情况下,构建了另一种分布式协议,其中可以同时确定时延的时间裕度。即使存在时延,也能得出充要的一致性结果。给出了仿真结果以证明我们所得到的一致性结果的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e873/9331186/a98c8c37e2d4/fpls-13-898183-g0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e873/9331186/26d36e0acc4d/fpls-13-898183-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e873/9331186/098b9ce4b0b7/fpls-13-898183-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e873/9331186/ba152c317a06/fpls-13-898183-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e873/9331186/1511955008eb/fpls-13-898183-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e873/9331186/9701630d07ac/fpls-13-898183-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e873/9331186/8a8ee25a2f12/fpls-13-898183-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e873/9331186/a98c8c37e2d4/fpls-13-898183-g0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e873/9331186/26d36e0acc4d/fpls-13-898183-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e873/9331186/098b9ce4b0b7/fpls-13-898183-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e873/9331186/ba152c317a06/fpls-13-898183-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e873/9331186/1511955008eb/fpls-13-898183-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e873/9331186/9701630d07ac/fpls-13-898183-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e873/9331186/8a8ee25a2f12/fpls-13-898183-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e873/9331186/a98c8c37e2d4/fpls-13-898183-g0007.jpg

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