<?xml version="1.1" encoding="utf-8"?>
<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">TACS</journal-id><journal-title-group><journal-title>Technology and Application of Computer Science</journal-title></journal-title-group><issn>2998-8926</issn><eissn>2998-8934</eissn><publisher><publisher-name>Art and Design</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.61369/TACS.2025030031</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>执行器故障下高阶非线性多智能体系统的非奇异有限时间控制</title><url>https://artdesignp.com/journal/TACS/2/3/10.61369/TACS.2025030031</url><author>刘达才,邓振杰</author><pub-date pub-type="publication-year"><year>2025</year></pub-date><volume>2</volume><issue>3</issue><history><date date-type="pub"><published-time>2025-02-14</published-time></date></history><abstract>本文首先研究了具有执行器故障的高阶非线性多智能体系统的非奇异有限时间约束控制问题。为了解决递归设计中出现的奇点问题，李雅普诺夫函数的设计采用了添加功率积分器的技术来代替平方。然后，利用模糊逻辑系统处理未知的非线性问题。为了实现对执行器故障的快速补偿，将分解法和界估计法相结合，设计了新的补偿律。最后，提出了一种新的有限时间控制方法来实现非奇异有限时间包围，并通过仿真得到了严格的验证。</abstract><keywords>模糊逻辑系统,多智能体系统,随机故障,非奇异有限时间控制</keywords></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>[1] D. Zhang and G. Feng, &amp;ldquo;A new switched system approach to leader&amp;ndash;follower consensus of heterogeneous linear multiagent systems with dos attack,&amp;rdquo; IEEE Transactions on Systems, Man, and Cybernetics:Systems, vol. 51, no. 2, pp. 1258&amp;ndash;1266, 2021.&amp;nbsp;[2] K.-L. Yin, Y.-F. Pu, and L. Lu, &amp;ldquo;Solving simo nonlinear systems with euler nonlinear filter,&amp;rdquo; IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 69, no. 3, pp. 1897&amp;ndash;1901, 2022.&amp;nbsp;[3] Y. Li, F. Qu, and S. Tong, &amp;ldquo;Observer-based fuzzy adaptive finite-time containment control of nonlinear multiagent systems with input delay,&amp;rdquo; IEEE Transactions on Cybernetics, vol. 51, no. 1, pp. 126&amp;ndash;137, 2021.&amp;nbsp;[4] Q. Wang, X. Dong, J. Yu, J. Lu, and Z. Ren, &amp;ldquo;Predefined finite-time &amp;uml; output containment of nonlinear multi-agent systems with leaders of unknown inputs,&amp;rdquo; IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 68, no. 8, pp. 3436&amp;ndash;3448, 2021.&amp;nbsp;[5] Y. Wang and Y. Song, &amp;ldquo;Fraction dynamic-surface-based neuroadaptive finite-time containment control of multiagent systems in nonaffine purefeedback form,&amp;rdquo; IEEE Transactions on Neural Networks and Learning Systems, vol. 28, no. 3, pp. 678&amp;ndash;689, 2017.&amp;nbsp;[6] H. Liang, Y. Zhang, T. Huang, and H. Ma, &amp;ldquo;Prescribed performance cooperative control for multiagent systems with input quantization,&amp;rdquo; IEEE Transactions on Systems, Man, and Cybernetics, vol. 50, no. 5, pp. 1810&amp;ndash;1819,.</p><pub-id pub-id-type="doi"/></element-citation></ref></ref-list></back></article>
