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

Manman Luo, Baibin Yang, Zhaolei Yan, Yuwen Shen and Manfeng Hu ()
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Manman Luo: School of Science, Jiangnan University, Wuxi 214122, China
Baibin Yang: School of Science, Jiangnan University, Wuxi 214122, China
Zhaolei Yan: School of Science, Jiangnan University, Wuxi 214122, China
Yuwen Shen: School of Science, Jiangnan University, Wuxi 214122, China
Manfeng Hu: School of Science, Jiangnan University, Wuxi 214122, China

Mathematics, 2024, vol. 12, issue 18, 1-16

Abstract: 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.

Keywords: dynamical bias; dynamic event-triggered mechanism; fading measurements; discrete nonlinear systems; non-fragile H ? state estimation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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