Resilient Model-Free Adaptive Iterative Learning Control for Nonlinear Systems Under Periodic DoS Attacks via a Fading Channel

被引：0

作者：

Yu, Wei ^{[1
]}

Wang, Rui ^{[1
]}

Bu, Xuhui ^{[1
]}

Hou, Zhongsheng ^{[2
]}

Wu, Zhonghua ^{[1
]}

机构：

[1] Henan Polytechnic University, School of Electrical Engineering and Automation, Jiaozuo,454003, China

[2] Qingdao University, School of Automation, Qingdao,266071, China

来源：

IEEE Transactions on Systems, Man, and Cybernetics: Systems | 2022年 / 52卷 / 07期

关键词：

Adaptive control systems - Denial-of-service attack - Nonlinear dynamical systems - Stochastic models - System stability - Dynamical systems - Stochastic systems - Learning algorithms - Two term control systems - Mobile robots - Stochastic control systems - Iterative methods - Machine design;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

This article studies the resilient control problem for a class of unknown nonlinear systems with fading measurements under malicious denial-of-service (DoS) attacks. The system output is assumed to be transmitted through a fading channel, where the fading phenomenon is described by a Rice fading model. The strategy of the attacker is to periodically interfere with the networked channels to reduce the success rate of data transmissions. First, a dynamic linearization method along the iteration domain is introduced to convert the nonlinear system into an equivalent data-related model. Then, a model-free adaptive iterative learning control (MFAILC) scheme is presented, which is independent of model information. The convergence of the MFAILC scheme is deduced theoretically and the influence of DoS attacks and stochastic fading phenomenon on system stability are also analyzed. Finally, the effectiveness of the design is verified by a numerical simulation and a trajectory tracking example of wheeled mobile robots (WMRs). © 2013 IEEE.

引用

页码：4117 / 4128