摘要
在拒绝服务攻击下,对一类高阶非线性多智能体系统的分布式模糊控制问题进行了研究。引入一种基于数据驱动的在线学习算法,学习参考系统的未知动态。针对Dos攻击设计一种弹性分布式观测器来观测参考系统状态。进一步设计基于高阶滤波器的改进观测器,并利用该观测器的状态和反步法设计分散自适应模糊控制器。通过理论分析证明所提出的方法,能够有效解决分布式弹性跟踪问题。最后,通过仿真实例验证了所提方法的有效性。
The distributed fuzzy control problem is investigated for a class of high-order fuzzy nonlinear multi-agent systems(MASs)under denial-of-service(DoS)attacks.Firstly,a data-driven online learning algorithm is introduced to learn the unknown dynamics of the reference system.A resilient distributed observer is designed to observe the state of the reference system even under the impact of DoS attacks.An improved observer based on high-order filter is further designed.The state of the observer and backstepping are utilized to design the decentralized adaptive fuzzy controller.The proposed method can effectively resolve the distributed resilient tracking problem by theoretical analysis proof.Finally,a simulation example is presented to demonstrate the effectiveness of the proposed method.
作者
张磊
张骜
卞鹏
陈侠
ZHANG Lei;ZHANG Ao;BIAN Peng;CHEN Xia(Shenyang Institute of Science and Technology,Shenyang 110167,China)
出处
《火力与指挥控制》
北大核心
2025年第9期27-35,44,共10页
Fire Control & Command Control
基金
国家自然科学基金资助项目(61906125)。
关键词
自适应模糊控制
弹性分布式控制
反步法
DOS攻击
多智能体
adaptive fuzzy control
resilient distributed control
backstepping design
DoS attack
multi-agent systems(MASs)
