Fault estimation for nonlinear systems with sensor gain degradation and stochastic protocol based on strong tracking filtering

IF 3.2 Q2 AUTOMATION & CONTROL SYSTEMS Systems Science & Control Engineering Pub Date : 2021-05-03 DOI:10.1080/21642583.2020.1833789
Jie Xu, Li Sheng, Ming Gao
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引用次数: 20

Abstract

This paper focuses on the fault estimation problem for a class of nonlinear systems with sensor gain degradation and stochastic protocol (SP) based on strong tracking filtering. The phenomenon of the sensor gain degradation is described by sequences of stochastic variables in a known interval. The stochastic protocol (SP) is used to deal with possible data conflicts in multi-signal transmission. The augmented system is constructed by combining the original system state vectors and the related faults into an augmented state vectors. The strong tracking filter (STF) is designed by introducing a fading factor into the filter structure to solve the problem of burst faults. Finally, a simulation example is given to verify the effectiveness and applicability of the proposed filter.
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基于强跟踪滤波和随机协议的传感器增益退化非线性系统故障估计
研究了一类具有传感器增益退化和基于强跟踪滤波的随机协议的非线性系统的故障估计问题。传感器增益退化现象由已知区间内的随机变量序列描述。随机协议(SP)用于处理多信号传输中可能出现的数据冲突。通过将原始系统状态向量和相关故障组合成增广状态向量来构造增广系统。强跟踪滤波器(STF)是通过在滤波器结构中引入衰落因子来解决突发故障问题的。最后,通过仿真实例验证了该滤波器的有效性和适用性。
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来源期刊
Systems Science & Control Engineering
Systems Science & Control Engineering AUTOMATION & CONTROL SYSTEMS-
CiteScore
9.50
自引率
2.40%
发文量
70
审稿时长
29 weeks
期刊介绍: Systems Science & Control Engineering is a world-leading fully open access journal covering all areas of theoretical and applied systems science and control engineering. The journal encourages the submission of original articles, reviews and short communications in areas including, but not limited to: · artificial intelligence · complex systems · complex networks · control theory · control applications · cybernetics · dynamical systems theory · operations research · systems biology · systems dynamics · systems ecology · systems engineering · systems psychology · systems theory
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