The Dynamic Event-Based Non-Fragile H∞ State Estimation for Discrete Nonlinear Systems with Dynamical Bias and Fading Measurement

The present study investigates non-fragile H∞ state estimation based on a dynamic event-triggered mechanism for a class of discrete time-varying nonlinear systems subject to dynamical bias and fading measurements. The dynamic deviation caused by unknown inputs is represented by a dynamic equation wi...

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Bibliographic Details
Published inMathematics (Basel) Vol. 12; no. 18; p. 2957
Main Authors Luo, Manman, Yang, Baibin, Yan, Zhaolei, Shen, Yuwen, Hu, Manfeng
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.09.2024
Subjects
Analysis
Bias
Communication
Data augmentation
Design
discrete nonlinear systems
Discrete time systems
dynamic event-triggered mechanism
dynamical bias
Dynamical systems
Energy consumption
Error analysis
Fading
Fading channels
fading measurements
H infinity
Linear matrix inequalities
Measurement
Noise (mathematics)
non-fragile H∞ state estimation
Nonlinear systems
Nonlinear theories
Sensors
Signal processing
Stability
Stability augmentation
State estimation
China
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Summary:The present study investigates non-fragile H∞ state estimation based on a dynamic event-triggered mechanism for a class of discrete time-varying nonlinear systems subject to dynamical bias and fading measurements. The dynamic deviation caused by unknown inputs is represented by a dynamic equation with bounded noise. Subsequently, the augmentation technique is employed and the dynamic event-triggered mechanism is introduced in the sensor-to-estimator channel to determine whether data should be transmitted or not, thereby conserving resources. Furthermore, an augmented state-dependent non-fragile state estimator is constructed considering gain perturbation of the estimator and fading measurements during network transmission. Sufficient conditions are provided based on Lyapunov stability and matrix analysis techniques to ensure exponential mean-square stability of the estimation error system while satisfying the H∞ disturbance fading level. The desired estimator gain matrix can be obtained by solving the linear matrix inequality (LMI). Finally, an example is presented to illustrate the effectiveness of the proposed method for designing estimators.
ISSN:2227-7390
2227-7390
DOI:10.3390/math12182957