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

页码：2584 / 2588

页数：5

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