scholarly journals Finite-Horizon Filtering for Markovian Jump Systems with Sensor Saturation**This work was supported in part by the National Natural Science Foundation of China under Grants 61374127 and 61422301, the Natural Science Foundation of Heilongjiang Province of China under Grant F201428, the Scientific and Technology Research Foundation of Heilongjiang Education Department under Grants 12541061 and 12541592, the 12th Five-Year-Plan in Key Science and Technology Research of agricultural bureau in Heilongjiang province of China under Grant HNK125B-04-03, the Doctoral Scientific Research Foundation of Heilongjiang Bayi Agricultural University under Grant XDB2014-12, Jiangsu Provincial Key Laboratory of E-business, Nanjing University of Finance and Economics JSEB201301.

2015 ◽  
Vol 48 (28) ◽  
pp. 668-673 ◽  
Author(s):  
Xianye Bu ◽  
Yang Lu ◽  
Gang Lu ◽  
Fan Yang ◽  
Yajing Yu
Keyword(s):  
Natural Science ◽  
Science And Technology ◽  
Scientific Research ◽  
Markovian Jump Systems ◽  
Heilongjiang Province ◽  
Technology Research ◽  
Markovian Jump ◽  
Education Department ◽  
Sensor Saturation ◽  
Jump Systems

scholarly journals Resilient H-infinity filtering for networked nonlinear Markovian jump systems with randomly occurring distributed delay and sensor saturation

2021 ◽  
Vol 26 (2) ◽  
pp. 187-206
Author(s):  
Venkatesan Nithya ◽  
Rathinasamy Sakthivel ◽  
Yong Ren
Keyword(s):  
Sufficient Conditions ◽  
Distributed Delay ◽  
Random Variable ◽  
Markovian Jump Systems ◽  
Linear Matrix ◽  
Markovian Jump ◽  
Missing Measurements ◽  
Sensor Saturation ◽  
Jump Systems ◽  
Nonlinear Markovian Jump Systems

The H∞ 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∞ 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.

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