前馈多智能体系统的分布式规定时间一致同构控制新框架。

IF 10.5 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Songsong Liu,Liuliu Zhang,Changchun Hua,Shuang Liu
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引用次数: 0

摘要

针对前馈多智能体系统(MASs)的规定时间全状态一致控制问题,提出了一个新的控制框架和分析方法。首先,为了解决由固有前馈非线性引起的障碍,设计的一个关键方面是创造性地构建每一步的坐标变换,并将规定的时间函数作为缩放因子。在此基础上,提出了一种新的前馈质量的规定时间同质控制框架。该框架的显著优点是结合了同构控制方法设计的低复杂性和状态尺度方案稳定性分析的简单性。然后,基于递归技术,设计了一种分布式的规定时间全状态共识控制器,使共识误差在任何规定时间达到平衡,并保证整个时间区间的稳定性。最后,通过液位控制谐振电路(LLCRC)系统对该算法进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A New Framework of Distributed Prescribed-Time Consensus Homogeneous Domination Control for Feedforward Multiagent Systems.
This article focuses on the prescribed-time full-state consensus control of feedforward multiagent systems (MASs), and a new framework and analysis are presented. First, to deal with the obstacle arising from inherent feedforward nonlinearity, a crucial aspect of the design is to creatively construct the coordinate transformation at each step and the prescribed-time function as a scaling factor. Subsequently, a novel prescribed-time homogeneous domination framework for feedforward MASs is developed. The significant advantage is that this framework combines the low complexity of homogeneous domination control method design with the simplicity of stability analysis for state-scale schemes. Then, based on the recursive techniques, a distributed prescribed-time full-state consensus controller is designed, which drives the consensus errors to reach equilibrium at any prescribed time and ensures the stability of the entire time interval. Finally, the proposed algorithm is validated through the liquid-level control resonant circuit (LLCRC) system.
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来源期刊
IEEE Transactions on Cybernetics
IEEE Transactions on Cybernetics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
25.40
自引率
11.00%
发文量
1869
期刊介绍: The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.
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