Neural-Adaptive Finite-Time Consensus Tracking of Singular Multiagent Systems With Actuator Attack

View at publisher
Authors: Xiaofan Liu, Yunyi Yan, Yongfang Xie, Xianxiang Wu
Cited by: 2
References: 31

Abstract

Since the actuator attack is an important threat to the complicated network, the problem of finite-time consensus tracking (FTCT) control for time-varying delay singular multiagent systems with actuator attack is investigated in this article. First, to approximate the states of the follower agents and design the sliding mode surfaces under actuator attack, a state observer is proposed. Then, the novel neural-adaptive distributed FTCT protocol and actuator attack estimation protocol are designed based on the radial basis function neural network estimation method. The sliding mode control with a partitioning strategy is adopted for the FTCT problem analysis of singular multiagent systems. The sufficient conditions and solving strategies of FTCT for singular multiagent systems over the whole finite-time interval are provided. Finally, the validity of FTCT for singular multiagent systems is verified by simulation examples.

Fields of Study & Subjects

Distributed Control Multi-Agent Systems Adaptive Dynamic Programming Control Neural Networks Stability and Synchronization

Publication details

Journal / source
IEEE Transactions on Neural Networks and Learning Systems
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
37
Issue
9
Pages
4093–4105
Publication date
16 February 2026
Language
EN