Data-Driven-Based Distributed Fuzzy Tracking Control for Nonlinear MASs Under DoS Attacks
Chao Deng, Fanzhi Meng, Xiangpeng Xie, Dong Yue, Wei‐Wei Che, Sha Fan
Abstract
In this paper, the distributed fuzzy tracking control problem is investigated for high-order fuzzy nonlinear multiagent systems (MASs) under denial-of-service attacks. The proposed method is distinct from existing approaches in that it can accommodate scenarios where the model parameters of the reference systems are unknown, and the MAS is high order and nonlinear. Specifically, a data-driven algorithm is first introduced to learn the unknown reference system matrix. Based on the learned matrix, a distributed resilient observer and an improved observer are, respectively, designed to guarantee that both observers can observe the reference system state and that the high-order derivative of the improved observer state exists. By using the improved observer state and its high-order derivatives, a decentralized adaptive fuzzy controller is designed for each agent based on the backstepping technique. It is shown that the distributed resilient tracking can be achieved by the proposed method. Finally, a simulation example is proposed to show the effectiveness of the developed method.