文献类型：期刊文献

英文题名：Quantized iterative learning control for nonlinear multi-agent systems with initial state error

作者：Zhang, Ting[1,2];Li, Ning[1];Chen, Jiaxi[2]

第一作者：Zhang, Ting

通讯作者：Zhang, T[1]

机构：[1]Henan Univ Econ & Law, Sch Math & Informat Sci, Zhengzhou 450046, Peoples R China;[2]Xidian Univ, Sch Math & Stat, Xian 710126, Peoples R China

第一机构：河南财经政法大学数学与信息科学学院

通讯机构：[1]corresponding author), Henan Univ Econ & Law, Sch Math & Informat Sci, Zhengzhou 450046, Peoples R China.|[1048425]河南财经政法大学数学与信息科学学院;[10484]河南财经政法大学;

年份：2024

卷号：186

外文期刊名：SYSTEMS & CONTROL LETTERS

收录：;EI(收录号：20241015670892);WOS:【SCI-EXPANDED(收录号:WOS:001200219100001)】；

基金：This work is supported by Youth Fund of the National Natural Science Foundation of China (Grant No. 62103136 and 62203342) and Outstanding Youth Fund of He'nan, China (Grant No. 222300420022).

语种：英文

外文关键词：Iterative learning control; Multi-agent systems; Quantization; Initial state; Non-smooth analysis

摘要：This paper proposed a consensus problem for nonlinear multi -agent systems (MAS) with logarithmic quantization and arbitrary initial states. By introducing the quantization, digital communication between signals is realized and the requirement of utilizing the digital channel more effective is also achieved. In order to eliminate the initial state errors introduced by the assumption of any initial value for every agent and to avoid the complexity for the common method of initial -state learning, a new method of control inputs compensation via iterative learning control (ILC) is introduced in this paper and the accurate tracking over the entire time period can be obtained asymptotically by the analysis of convergence. The effectiveness of the designed protocol is verified by some numerical simulations.