Event-based recursive filtering for time-delayed stochastic nonlinear systems with missing measurements

2017 ◽  
Vol 134 ◽  
pp. 158-165 ◽  
Author(s):  
Jingyang Mao ◽  
Derui Ding ◽  
Yan Song ◽  
Yurong Liu ◽  
Fuad E. Alsaadi
Keyword(s):  
Nonlinear Systems ◽  
Stochastic Nonlinear Systems ◽  
Missing Measurements ◽  
Recursive Filtering ◽  
Event Based

Event-based resilient filtering for stochastic nonlinear systems via innovation constraints

2021 ◽  
Vol 546 ◽  
pp. 512-525
Author(s):  
Ying Sun ◽  
Derui Ding ◽  
Hongli Dong ◽  
Hongjian Liu
Keyword(s):  
Nonlinear Systems ◽  
Stochastic Nonlinear Systems ◽  
Event Based

scholarly journals Estimation for Stochastic Nonlinear Systems with Randomly Distributed Time-Varying Delays and Missing Measurements

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Yan Che ◽  
Huisheng Shu ◽  
Xiu Kan
Keyword(s):  
Nonlinear Systems ◽  
Estimation Error ◽  
Linear Matrix ◽  
Stochastic Nonlinear Systems ◽  
Time Varying ◽  
Matrix Inequality ◽  
Missing Measurements ◽  
Design Procedures ◽  
Mean Square Stability ◽  
The Mean

The estimation problem is investigated for a class of stochastic nonlinear systems with distributed time-varying delays and missing measurements. The considered distributed time-varying delays, stochastic nonlinearities, and missing measurements are modeled in random ways governed by Bernoulli stochastic variables. The discussed nonlinearities are expressed by the statistical means. By using the linear matrix inequality method, a sufficient condition is established to guarantee the mean-square stability of the estimation error, and then the estimator parameters are characterized by the solution to a set of LMIs. Finally, a simulation example is exploited to show the effectiveness of the proposed design procedures.

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