Neural networks-based iterative learning control consensus for periodically time-varying multi-agent systems
作者机构:School of Mathematics and StatisticsXidian UniversityXi'an 710071China School of Aerospace Science and TechnologyXidian UniversityXi'an 710071China
出 版 物:《Science China(Technological Sciences)》 (中国科学(技术科学英文版))
年 卷 期:2024年第67卷第2期
页 面:464-474页
核心收录:
学科分类:12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0805[工学-材料科学与工程(可授工学、理学学位)] 0835[工学-软件工程] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术(可授工学、理学学位)] 080201[工学-机械制造及其自动化]
基 金:supported by the National Natural Science Foundation of China(Grant Nos.62203342,62073254,92271101,62106186,and62103136) the Fundamental Research Funds for the Central Universities(Grant Nos.XJS220704,QTZX23003,and ZYTS23046) the Project funded by China Postdoctoral Science Foundation(Grant No.2022M712489) the Natural Science Basic Research Program of Shaanxi(Grant Nos.2023-JC-YB-585 and 2020JM-188)
主 题:multi-agent systems adaptive iterative learning control nonlinearly parameterized dynamics Fourier series expansion neural networks
摘 要:In this paper,the problem of adaptive iterative learning based consensus control for periodically time-varying multi-agent systems is studied,in which the dynamics of each follower are driven by nonlinearly parameterized terms with periodic *** networks and Fourier base expansions are introduced to describe the periodically time-varying dynamic *** this basis,an adaptive learning parameter with a positively convergent series term is constructed,and a distributed control protocol based on local signals between agents is designed to ensure accurate consensus of the closed-loop ***,consensus algorithm is generalized to solve the formation control ***,simulation experiments are implemented through MATLAB to demonstrate the effectiveness of the method used.