Adaptive Event-Triggered Fault Detection for Fuzzy Stochastic Systems With Missing Measurements

Ning, Zhaoke; Yu, Jinyong; Pan, Yingnan; Li, Hongyi

doi:10.1109/tfuzz.2017.2780799

Cited by 70 publications

(29 citation statements)

References 46 publications

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“…The membership functions of controller (6) are not the same as the fuzzy plant (2) due to the utilization of IT2 T-S fuzzy model, which lead to imperfect premise matching [29]. Compared with the traditional type-1 T-S fuzzy model [21], the imperfect prefect premise is not only improving the flexibility of designing fuzzy controller, but also reducing the calculation burden.…”

Section: Remarkmentioning

confidence: 99%

“…In this paper, the slack matrix is adopted to handle the problem of mismatched membership functions which cannot be solved by the existing results [8,21,41]. In order to improve the flexibility of the controller, an IT2 fuzzy model was adopted in [25], and the sensor saturation was also considered in [25].…”

Section: Remarkmentioning

confidence: 99%

“…Nevertheless, uncertainties often exist in plants, hence, traditional type-1 T-S fuzzy method [8,21] whose membership functions are determined lose the ability to handle uncertain membership grades. To this end, a novel interval type-2 (IT2) T-S fuzzy model was proposed by H.K.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Reliable Dissipative Interval Type-2 Fuzzy Control for Nonlinear Systems with Stochastic Incomplete Communication Route and Actuator Failure

Pan

Zhang

et al. 2020

Int. J. Fuzzy Syst.

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Section: Remarkmentioning

confidence: 99%

Section: Remarkmentioning

confidence: 99%

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Reliable Dissipative Interval Type-2 Fuzzy Control for Nonlinear Systems with Stochastic Incomplete Communication Route and Actuator Failure

Pan

Zhang

et al. 2020

Int. J. Fuzzy Syst.

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“…Currently, sampled‐data control problems have attracted much attention and been extensively studied . For the traditional sampled‐data systems, the signal that is sampled by the fixed time interval is transmitted into the controller at each sampling instant.…”

Section: Introductionmentioning

confidence: 99%

“…13 Currently, sampled-data control problems have attracted much attention and been extensively studied. [14][15][16][17] For the traditional sampled-data systems, the signal that is sampled by the fixed time interval is transmitted into the controller at each sampling instant. Owing to the fact that the controller signal does not need to be updated, when the systems operate in ideal state, periodic updates of controller may waste computation resources and limited network resources (LNRs).…”

Section: Introductionmentioning

confidence: 99%

Observer‐based event‐triggered control for singularly perturbed systems with saturating actuator

Yan

Yang

et al. 2019

Intl J Robust & Nonlinear

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Summary This paper investigates an observer‐based event‐triggered control problem of singularly perturbed systems with saturating actuator. A strategy that consists of an observer‐based controller (OBC) and an event‐triggered mechanism (ETM) is considered. Firstly, sufficient conditions, which guarantee that the saturated SPSs are asymptotically stable excluding Zeno phenomenon, are derived via constructing an ε‐dependent Lyapunov‐Krasovskii functional. Then, the OBC and ETM are designed simultaneously based on the aforementioned criteria. Furthermore, an estimate of the basin of attraction and an ε‐bound are given by solving an optimization problem in the form of LMIs. Finally, an electric circuit system and a numerical example are presented to demonstrate the merits of the obtained method.

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Retracted: State estimation of Takagi‐Sugeno fuzzy system in networked control system with stochastic time delays under unknown attacks

Shamrooz

2021

Adaptive Control & Signal

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This article concerns the event‐triggered fuzzy filter design for Takagi‐Sugeno (T‐S) fuzzy systems subject to deception attacks under the stochastic multiple time‐varying delays. A sequence of random variables, which are mutually independent but obey the Bernoulli distribution, is introduced to account for the randomly occurring communication delays. In order to efficiently utilize limited network communication bandwidth resources, the event‐triggering scheme is adopted. A fuzzy filter with the attacked input signal is presented. Moreover, due to communication delays caused by event‐triggering schemes and transmission, the filter adopts non‐synchronous premise variables with the system. Then, by utilizing a model transformation technique, the fuzzy systems are developed. Furthermore, using the piecewise Lyapunov functional method technique, the resulting criterion provides sufficient conditions to ensure that fuzzy systems under deception attacks are stochastically stable with an H∞ performance. Accordingly, the conditions for the co‐design of the fuzzy filter and event‐triggering schemes are given. Finally, numerical simulation with the industrial process provided to verify the proposed event‐triggered design.

show abstract

Adaptive Event-Triggered Fault Detection for Fuzzy Stochastic Systems With Missing Measurements

Cited by 70 publications

References 46 publications

Reliable Dissipative Interval Type-2 Fuzzy Control for Nonlinear Systems with Stochastic Incomplete Communication Route and Actuator Failure

Reliable Dissipative Interval Type-2 Fuzzy Control for Nonlinear Systems with Stochastic Incomplete Communication Route and Actuator Failure

Observer‐based event‐triggered control for singularly perturbed systems with saturating actuator

Retracted: State estimation of Takagi‐Sugeno fuzzy system in networked control system with stochastic time delays under unknown attacks

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