迭代学习控制
非线性系统
线性化
遏制(计算机编程)
计算机科学
有界函数
方案(数学)
控制理论(社会学)
网络拓扑
自适应控制
过程(计算)
趋同(经济学)
数学优化
反馈线性化
控制(管理)
人工智能
拓扑(电路)
数学
物理
组合数学
操作系统
数学分析
经济
程序设计语言
量子力学
经济增长
作者
Tong Liu,Zhongsheng Hou
标识
DOI:10.1016/j.neucom.2022.09.154
摘要
A novel model-free adaptive iterative learning control scheme is proposed for the containment control problem of unknown heterogeneous nonlinear multi-agent systems (MASs) with bounded measurable and unmeasurable disturbances. In details, the proposed scheme includes following parts. First, the agent dynamics are transformed into a partial form dynamic linearization data model along the iteration axis by using the novel concept of the pseudo gradient. Second, the distributed containment control scheme is designed for MASs under fixed topology based on the obtained data model at each working point. Then, the scheme is extended to the case of iteration-switching topologies. Finally, the convergences have been proved by rigorous mathematical analysis. The whole containment control process is characterized with data-driven nature by only using the input and output data. Simulation results illustrate the effectiveness of the schemes.
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