残余物
算法
稳健性(进化)
计算机科学
灵敏度(控制系统)
故障检测与隔离
人工智能
化学
电子工程
生物化学
基因
工程类
执行机构
作者
Hao Jia,Wenchengyu Ji,Xiangpeng Xie,Shenquan Wang
出处
期刊:Neurocomputing
[Elsevier BV]
日期:2023-03-22
卷期号:535: 134-143
被引量:6
标识
DOI:10.1016/j.neucom.2023.03.026
摘要
This paper proposes an H∞/H∞ optimization technique to distributed fault detection (FD) for multi-agent systems (MASs). To simultaneously consider the effects of unknown disturbances and faults in the MASs and event-triggered transmission errors (ETTEs) on the residual signal, a residual generator related to the event-triggered threshold coefficient is designed. The generated residuals achieve the best compromise between robustness to unknown disturbances and sensitivity to faults. The obtained results have a better detection performance by using H∞/H∞ optimization technique compared with other optimized schemes. In addition, the applicability of the proposed H∞/H∞ optimized distributed FD scheme is verified by the simulation of a vehicle lateral dynamic system.
科研通智能强力驱动
Strongly Powered by AbleSci AI