Adaptive fault estimation for T-S fuzzy systems with unmeasurable premise variables

Liu, Shaokun; Li, Xiaojian; Wang, Heng; Yan, Jianguo

doi:10.1186/s13662-018-1571-5

Cited by 9 publications

(6 citation statements)

References 27 publications

(34 reference statements)

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“…The second-order extended system according to the following equations is yielded by substituting (1) and 7into (5) and substituting (1) and (8) into (6):…”

Section: The Second-order Extended Systemmentioning

confidence: 99%

“…During the last three decades, the estimation problem of input noise has become an active field in industry and has a wide range of applications in fault detection, petroleum prospecting, image restoration, speech processing, and so forth [1][2][3][4][5][6]. The Kalman deconvolution filter approach applied to the reflection coefficient sequence estimate in oil exploration was first proposed in [3].…”

Section: Introductionmentioning

confidence: 99%

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A study on input noise second-order filtering and smoothing of linear stochastic discrete systems with packet dropouts

Zhao

et al. 2020

Adv Differ Equ

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We investigate non-Gaussian noise second-order filtering and fixed-order smoothing problems for non-Gaussian stochastic discrete systems with packet dropouts. We present a novel Kalman-like nonlinear non-Gaussian noise estimation approach based on the packet dropout probability distribution and polynomial filtering technique. By means of properties of Kronecker product we first introduce a second-order polynomial extended system and then analyze the means and variances of the Kronecker powers of the extended system noises. To generate noise estimators in forms of filtering and smoothing, we use the innovation approach. We give an example to illustrate that the presented algorithm has better robustness against packet dropouts than conventional linear minimum variance estimation.

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“…The second-order extended system according to the following equations is yielded by substituting (1) and 7into (5) and substituting (1) and (8) into (6):…”

Section: The Second-order Extended Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A study on input noise second-order filtering and smoothing of linear stochastic discrete systems with packet dropouts

Zhao

et al. 2020

Adv Differ Equ

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show abstract

“…In [4], the authors proposed a method to design an observer for systems subjected to unknown inputs and disturbances. Actuator fault estimation in presence of sensor disturbances using an adaptive observer has been treated in [23]. An observer-based controller for robust stabilization of uncertain TS systems is presented in [37].…”

Section: Introductionmentioning

confidence: 99%

Observer design for Interconnected Takagi-Sugeno systems with Immeasurable Premise Variables

Ouhib

Kara

2022

Preprint

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This paper deals with observer design for a class of Interconnected Takagi-Sugeno systems with Immeasurable Premise Variables. Asymptotic stability and -stability of Luenberger-like Interconnected Multiple Observers are examined. Finsler’s Lemma is used to relax -stability conditions through the introduction of additional slack variables. The designed conditions are expressed as Linear Matrix Inequalities. The proposed approaches are applied in simulation to a Proton Exchange Membrane Fuel Cell (PEMFC) system and a four-tank system.

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“…By fuzzy blending of linear representations with appropriate membership functions, the overall fuzzy model of the system is achieved, which greatly simplifies the analysis and control for complex nonlinear systems. Therefore, excellent results in FE and FTC problems of T-S fuzzy systems are developed in [11][12][13][14][15][16][17]. In [18], a FTC is designed for TS fuzzy systems subject to actuator faults.…”

Section: Introductionmentioning

confidence: 99%

Robust Static Output-Feedback Fault Tolerant Control for a Class of T-S Fuzzy Systems using Adaptive Sliding Mode Observer Approach

Dhahri¹,

Alaïa²

2020

Adv. sci. technol. eng. syst. j.

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In this paper, the problems of actuator and sensor fault estimation (FE) and fault-tolerant control (FTC) for uncertain nonlinear systems represented by Takagi-Sugeno (T-S) fuzzy models are investigated. First, a robust fuzzy adaptive sliding mode observer (SMO) is designed to simultaneously estimate system states and both actuator and sensor faults. Then, using the obtained on-line FE information, a static output-feedback fault-tolerant control (SOFFTC) is developed to compensate the fault effects and stabilize the closed-loop system. Moreover, sufficient conditions for the existence of the proposed observer and controller are given in terms of linear matrix inequalities (LMIs). The robustness against uncertainties is treated using the H ∞ optimization technique to attenuate its effect on the estimation error. Finally, the simulation results of nonlinear inverted pendulum with cart system validate the efficiency of the proposed method.

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Adaptive fault estimation for T-S fuzzy systems with unmeasurable premise variables

Cited by 9 publications

References 27 publications

A study on input noise second-order filtering and smoothing of linear stochastic discrete systems with packet dropouts

A study on input noise second-order filtering and smoothing of linear stochastic discrete systems with packet dropouts

Observer design for Interconnected Takagi-Sugeno systems with Immeasurable Premise Variables

Robust Static Output-Feedback Fault Tolerant Control for a Class of T-S Fuzzy Systems using Adaptive Sliding Mode Observer Approach

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