Filter Design for Positive T–S Fuzzy Continuous-Time Systems With Time Delay Using Piecewise-Linear Membership Functions

Meng, Aiwen; Lam, Hak‐Keung; Liu, Fucai; Yang, Yingjie

doi:10.1109/tfuzz.2020.3001744

Cited by 18 publications

(7 citation statements)

References 58 publications

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“…By combining (35) with ( 36), ( 21) can be obtained. From (21), the inequality (22) with MFs w i (x)m j (x) can be obtained. Hence, combining with (32), p i=1 c j=1 w i (x)m j (y)λ T Āij (x, y) ≺ 0 can be proved, which means V (t) < 0.…”

Section: A Basic Stability Analysis Of Positive L 1 -Gain Pfof Contro...mentioning

confidence: 99%

“…But this method will cause some limitations for the design of fuzzy controllers, for instance, it will increase the complexity of controller design if the plants are complex, especially, when the number of the fuzzy rules is high or the type of membership functions is complicated. To overcome these drawbacks, imperfect premise matching concept was firstly proposed in [21] and employed in [22] to investigate the filtering problems for the positive T-S fuzzy systems. Although it could lead to conservatism, it is worth mentioning that the well-known membership-function-dependent (MFD) analysis proposed by H. K. Lam [23]- [26] provided a great help to reduce the conservatism by taking the information of membership functions (MFs) into the stability analysis.…”

Section: Introductionmentioning

confidence: 99%

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Membership-Function-Dependent Design of $L_1$-Gain Output-Feedback Controller for Stabilization of Positive Polynomial Fuzzy Systems

Meng

Lam

Liu

et al. 2022

IEEE Trans. Fuzzy Syst.

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Section: A Basic Stability Analysis Of Positive L 1 -Gain Pfof Contro...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Membership-Function-Dependent Design of $L_1$-Gain Output-Feedback Controller for Stabilization of Positive Polynomial Fuzzy Systems

Meng

Lam

Liu

et al. 2022

IEEE Trans. Fuzzy Syst.

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“…In recent years, the topics on Takagi-Sugeno (T-S) fuzzy theory have been received the attention of a wide range due to its simple and convenient advantages. [1][2][3][4][5] The T-S fuzzy model can be used to ap7777proximate the nonlinear systems involved in complex structures into several linear subsystems by utilizing a set of IF-THEN rules. As a result, there are many results on fuzzy theory that have been proposed in the literature and employed in practical industrial systems.…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, the topics on Takagi‐Sugeno (T‐S) fuzzy theory have been received the attention of a wide range due to its simple and convenient advantages 1‐5 . The T‐S fuzzy model can be used to ap7777proximate the nonlinear systems involved in complex structures into several linear subsystems by utilizing a set of IF‐THEN rules.…”

Section: Introductionmentioning

confidence: 99%

Security‐based fault detection filtering design for fuzzy singular semi‐Markovian jump systems via improved dynamic event‐triggering and quantization protocols

Kong,

Luo,

Cheng

et al. 2023

Adaptive Control & Signal

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SummaryThis article concerns the problem of event‐protocol‐based asynchronous fault detection filtering design for discrete‐time fuzzy singular semi‐Markovian jump systems subjected to system parameters uncertainties, unmatched one‐sided Lipschitz nonlinearities and multi‐cyber‐attacks. First, a well‐designed model structure is proposed to integrate two dynamic quantizers and an improved dynamic event‐triggered protocol into a unified framework to reduce the amount of data in the network transmission and rationalize the use of limited network communication bandwidth resources. Especially, the event‐triggering threshold parameter can be continuously adjusted over the time based on the fluctuation of the network signal. Second, a novel triple‐cyber‐attacks platform is established, of which including random deception attacks, random replay attacks and aperiodic DoS attacks. And with help of the extended decoupling strategy and iterative techniques, the co‐design conditions of the stochastic admissibility with a level of performance are derived for the fault filtering error systems. Finally, two examples are provided to demonstrate the effectiveness and feasibility of the proposed algorithm.

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“…The work in [30] discussed the optimal L 1 -gain and L ∞ -gain controller design and synthesis problem for positive nonlinear systems on the strength of T-S fuzzy models. A filter design with satisfying L 1 performance for positive T-S fuzzy models was studied in [31]. To the best of authors' knowledge, hitherto few researchers aim at the event-triggered mechanism on positive T-S fuzzy systems, which greatly motivates this study.…”

Section: Introductionmentioning

confidence: 99%

Stability and Stabilization of Fuzzy Event-Triggered Control for Positive Nonlinear Systems

Wang,

Meng,

Lam

et al. 2023

Int. J. Fuzzy Syst.

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This paper is concerned with the stabilization and event-triggered control for positive nonlinear systems in terms of Takagi-Sugeno (T-S) fuzzy models. By employing the unique positivity of positive systems, a new event-triggered mechanism is introduced to select necessary signals so that the communication resources can be saved effectively while guaranteeing the system performance. It is different from the traditional eventtriggered mechanism that is designed in the quadratic form for general systems, the one adopted in this paper is in linear form which is beneficial to facilitate the stability analysis in terms of a linear copositive Lyapunov function. However, the tricky non-convex problem makes controller design extremely challenging. For handling this issue, the matrix decomposition technique plays a very important part in designing the feedback

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Filter Design for Positive T–S Fuzzy Continuous-Time Systems With Time Delay Using Piecewise-Linear Membership Functions

Cited by 18 publications

References 58 publications

Membership-Function-Dependent Design of $L_1$-Gain Output-Feedback Controller for Stabilization of Positive Polynomial Fuzzy Systems

Membership-Function-Dependent Design of $L_1$-Gain Output-Feedback Controller for Stabilization of Positive Polynomial Fuzzy Systems

Security‐based fault detection filtering design for fuzzy singular semi‐Markovian jump systems via improved dynamic event‐triggering and quantization protocols

Stability and Stabilization of Fuzzy Event-Triggered Control for Positive Nonlinear Systems

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