首页|动态事件触发策略下非线性离散奇异系统的抗野值分布式融合滤波

动态事件触发策略下非线性离散奇异系统的抗野值分布式融合滤波

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本文研究一类多传感器非线性奇异系统在动态事件触发策略下的抗野值分布式融合滤波问题.采用自适应饱和函数设计滤波器可以有效减轻数据传输中测量野值的影响.为进一步节省每个传感器节点的能耗,提高资源利用效率,利用动态事件触发策略调节数据传输频率.对于所处理的非线性奇异系统,本文主要目的是在测量野值和动态事件触发策略影响下构造局部抗野值滤波器,并通过求解差分方程得到滤波误差协方差矩阵的局部上界.同时,所设计的滤波器增益可以确保该局部上界迹取值最小.此外,根据局部滤波器及其上界、逆协方差交叉融合准则,提出可以降低数据传输频率和测量野值的影响的分布式融合滤波算法.在均方意义下,讨论滤波误差的一致有界性并给出相应的充分条件.最后,通过仿真例子验证算法的有效性.
Outlier-resistant distributed fusion filtering for nonlinear discrete-time singular systems under a dynamic event-triggered scheme
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.

Distributed fusion filteringMulti-sensor nonlinear singular systemsDynamic event-triggered schemeOutlier-resistant filterUniform boundedness

胡志斌、胡军、陈才、刘宏建、伊枭剑

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哈尔滨理工大学应用数学系,中国哈尔滨市,150080

哈尔滨理工大学黑龙江省复杂系统优化控制与智能分析重点实验室,中国哈尔滨市,150080

哈尔滨理工大学自动化学院,中国哈尔滨市,150080

安徽工程大学数理学院,中国芜湖市,241000

北京理工大学机电学院,中国 北京市,100081

北京理工大学长三角研究院,中国嘉兴市,314003

北京理工大学唐山研究院,中国唐山市,063099

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分布式融合滤波 多传感器非线性奇异系统 动态事件触发策略 抗野值滤波器 一致有界

National Natural Science Foundation of ChinaNatural Science Foundation of Heilongjiang Province of ChinaNational Highend Foreign Experts Recruitment Plan of ChinaAlexander von Humboldt Foundation of Germany

12171124ZD2022F003G2023012004L

2024

10.1631/FITEE.2300508

信息与电子工程前沿(英文)
浙江大学

信息与电子工程前沿(英文)

CSTPCD
影响因子：0.371
ISSN：2095-9184
年,卷(期)：2024.25(2)
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