Non-fragile estimation for discrete-time T-S fuzzy systems with event-triggered protocol

Fei Han; Wei Gao; Hongyu Gao; Qianqian He

Kybernetika (2020)

  • Volume: 56, Issue: 1, page 57-80
  • ISSN: 0023-5954

Abstract

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This paper investigates the non-fragile state estimation problem for a class of discrete-time T-S fuzzy systems with time-delays and multiple missing measurements under event-triggered mechanism. First of all, the plant is subject to the time-varying delays and the stochastic disturbances. Next, a random white sequence, the element of which obeys a general probabilistic distribution defined on [ 0 , 1 ] , is utilized to formulate the occurrence of the missing measurements. Also, an event generator function is employed to regulate the transmission of data to save the precious energy. Then, a non-fragile state estimator is constructed to reflect the randomly occurring gain variations in the implementing process. By means of the Lyapunov-Krasovskii functional, the desired sufficient conditions are obtained such that the Takagi-Sugeno (T-S) fuzzy estimation error system is exponentially ultimately bounded in the mean square. And then the upper bound is minimized via the robust optimization technique and the estimator gain matrices can be calculated. Finally, a simulation example is utilized to demonstrate the effectiveness of the state estimation scheme proposed in this paper.

How to cite

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Han, Fei, et al. "Non-fragile estimation for discrete-time T-S fuzzy systems with event-triggered protocol." Kybernetika 56.1 (2020): 57-80. <http://eudml.org/doc/297328>.

@article{Han2020,
abstract = {This paper investigates the non-fragile state estimation problem for a class of discrete-time T-S fuzzy systems with time-delays and multiple missing measurements under event-triggered mechanism. First of all, the plant is subject to the time-varying delays and the stochastic disturbances. Next, a random white sequence, the element of which obeys a general probabilistic distribution defined on $[0,1]$, is utilized to formulate the occurrence of the missing measurements. Also, an event generator function is employed to regulate the transmission of data to save the precious energy. Then, a non-fragile state estimator is constructed to reflect the randomly occurring gain variations in the implementing process. By means of the Lyapunov-Krasovskii functional, the desired sufficient conditions are obtained such that the Takagi-Sugeno (T-S) fuzzy estimation error system is exponentially ultimately bounded in the mean square. And then the upper bound is minimized via the robust optimization technique and the estimator gain matrices can be calculated. Finally, a simulation example is utilized to demonstrate the effectiveness of the state estimation scheme proposed in this paper.},
author = {Han, Fei, Gao, Wei, Gao, Hongyu, He, Qianqian},
journal = {Kybernetika},
keywords = {Takagi--Sugeno fuzzy system; exponentially ultimately boundness; non-fragile estimation; robust optimization},
language = {eng},
number = {1},
pages = {57-80},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Non-fragile estimation for discrete-time T-S fuzzy systems with event-triggered protocol},
url = {http://eudml.org/doc/297328},
volume = {56},
year = {2020},
}

TY - JOUR
AU - Han, Fei
AU - Gao, Wei
AU - Gao, Hongyu
AU - He, Qianqian
TI - Non-fragile estimation for discrete-time T-S fuzzy systems with event-triggered protocol
JO - Kybernetika
PY - 2020
PB - Institute of Information Theory and Automation AS CR
VL - 56
IS - 1
SP - 57
EP - 80
AB - This paper investigates the non-fragile state estimation problem for a class of discrete-time T-S fuzzy systems with time-delays and multiple missing measurements under event-triggered mechanism. First of all, the plant is subject to the time-varying delays and the stochastic disturbances. Next, a random white sequence, the element of which obeys a general probabilistic distribution defined on $[0,1]$, is utilized to formulate the occurrence of the missing measurements. Also, an event generator function is employed to regulate the transmission of data to save the precious energy. Then, a non-fragile state estimator is constructed to reflect the randomly occurring gain variations in the implementing process. By means of the Lyapunov-Krasovskii functional, the desired sufficient conditions are obtained such that the Takagi-Sugeno (T-S) fuzzy estimation error system is exponentially ultimately bounded in the mean square. And then the upper bound is minimized via the robust optimization technique and the estimator gain matrices can be calculated. Finally, a simulation example is utilized to demonstrate the effectiveness of the state estimation scheme proposed in this paper.
LA - eng
KW - Takagi--Sugeno fuzzy system; exponentially ultimately boundness; non-fragile estimation; robust optimization
UR - http://eudml.org/doc/297328
ER -

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