Outlier-resistant distributed fusion filtering for nonlinear discrete-time singular systems under a dynamic event-triggered scheme  

作　　者：Zhibin HU Jun HU Cai CHEN Hongjian LIU Xiaojian YI 

机构地区：[1]Department of Applied Mathematics,Harbin University of Science and Technology,Harbin,150080,China [2]Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems,Harbin University of Science and Technology,Harbin,150080,China [3]School of Automation,Harbin University of Science and Technology,Harbin,150080,China [4]School of Mathematics and Physics,Anhui Polytechnic University,Wuhu,241000,China [5]School of Mechatronical Engineering,Beijing Institute of Technology,Beijing,100081,China [6]Yangtze Delta Region Academy of Beijing Institute of Technology,Jiaxing,314003,China [7]Tangshan Research Institute,Beijing Institute of Technology,Tangshan,063099,China

出　　处：《Frontiers of Information Technology & Electronic Engineering》2024年第2期237-249,共13页信息与电子工程前沿（英文版）

基　　金：Project supported by the National Natural Science Foundation of China(No.12171124);the Natural Science Foundation of Heilongjiang Province of China(No.ZD2022F003);the National High-end Foreign Experts Recruitment Plan of China(No.G2023012004L);the Alexander von Humboldt Foundation of Germany。

摘　　要：This paper investigates the problem of outlier-resistant distributed fusion filtering(DFF)for a class of multi-sensor nonlinear singular systems(MSNSSs)under a dynamic event-triggered scheme(DETS).To relieve the effect of measurement outliers in data transmission,a self-adaptive saturation function is used.Moreover,to further reduce the energy consumption of each sensor node and improve the efficiency of resource utilization,a DETS is adopted to regulate the frequency of data transmission.For the addressed MSNSSs,our purpose is to construct the local outlier-resistant filter under the effects of the measurement outliers and the DETS;the local upper bound(UB)on the filtering error covariance(FEC)is derived by solving the difference equations and minimized by designing proper filter gains.Furthermore,according to the local filters and their UBs,a DFF algorithm is presented in terms of the inverse covariance intersection fusion rule.As such,the proposed DFF algorithm has the advantages of reducing the frequency of data transmission and the impact of measurement outliers,thereby improving the estimation performance.Moreover,the uniform boundedness of the filtering error is discussed and a corresponding sufficient condition is presented.Finally,the validity of the developed algorithm is checked using a simulation example.

关 键 词：Distributed fusion filtering Multi-sensor nonlinear singular systems Dynamic event-triggered scheme Outlier-resistant filter Uniform boundedness 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]