Resilient H∞ filtering for networked nonlinear Markovian jump systems with randomly occurring distributed delay and sensor saturation

被引:2
作者
Nithya, Venkatesan [1 ]
Sakthivel, Rathinasamy [1 ]
Ren, Yong [2 ]
机构
[1] Bharathiar Univ, Dept Appl Math, Coimbatore 641046, Tamil Nadu, India
[2] Anhui Normal Univ, Dept Math, Wuhu 241000, Peoples R China
来源
NONLINEAR ANALYSIS-MODELLING AND CONTROL | 2021年 / 26卷 / 02期
关键词
discrete-time networked Markovian jump systems; randomly occurring distributed delay; sensor saturation; quantization effects; missing measurements; PARAMETER-VARYING SYSTEMS; NEURAL-NETWORKS; FUZZY-SYSTEMS; DISCRETE; DESIGN; PROBABILITIES;
D O I
10.15388/namc.2021.26.22355
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The H-infinity filtering problem for a class of networked nonlinear Markovian jump systems subject to randomly occurring distributed delays, nonlinearities, quantization effects, missing measurements and sensor saturation is investigated in this paper. The measurement missing phenomenon is characterized via a random variable obeying the Bernoulli stochastic distribution. Moreover, due to bandwidth limitations, the measurement output is quantized using a logarithmic quantizer and then transmitted to the filter. Further, the output measurements are affected by sensor saturation since the communication links between the system and the filter are unreliable and is described by sector nonlinearities. The objective of this work is to design a quantized resilient filter that guarantees not only the stochastic stability of the augmented filtering error system but also a prespecified level of H-infinity performance. Sufficient conditions for the existence of desired filter are established with the aid of proper Lyapunov-Krasovskii functional and linear matrix inequality approach together with stochastic analysis theory. Finally, a numerical example is presented to validate the developed theoretical results.
引用
收藏
页码:187 / 206
页数:20
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