Model free Adaptive Predictive Control with Prescribed Performance for Discrete-Time Nonlinear Multiagent Systems

被引：0
|
作者：
Yang, Yijie [1 ]
Liu, Dong [1 ]
机构：
[1] Shenyang Aerosp Univ, Sch Automat, Shenyang 110135, Peoples R China
来源：
2023 35TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC | 2023年
基金：
中国国家自然科学基金;
关键词：
Model Free Adaptive Predictive Control; Multiagent Systems; Prescribed Performance Control;
D O I：
10.1109/CCDC58219.2023.10326489
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This article is devoted to investigating model-free adaptive predictive control scheme based on prescribed performance for nonlinear multiagent systems (MASs). A novel tangent-type error transformation function is proposed for mapping performance indicator from constrained to unconstrained. Compared with the common logarithmic-type error transformation function, the computational complexity is reduced. Meanwhile, the convergence of distributed measurement error among agents to a predefined area is achieved. Furthermore, the proposed scheme is data-driven method based on compact form dynamic linearization without any model information. Theoretical analysis ensures the consensus of multiple agents and the analysis result is verified by simulation.
引用
收藏
页码：2584 / 2588
页数：5
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