Free-matrix-based integral inequality for stability analysis of uncertain T-S fuzzy systems with time-varying delay

Luo, Wei; Yang, Jun; Zhao, Xin

doi:10.1007/s12555-015-0228-3

Cited by 6 publications

(3 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Regarding conservatism, the WBII is employed in literature to bound single integral terms that appeared in the derivative of the LKF. In this paper, both WBII and a generalized version of WBII, 35 namely GFWMI is utilized, since the use of GFWMI brings several advantages to the main result. Introducing certain free matrices results in more degrees of freedom in the derived result.…”

Section: Resultsmentioning

confidence: 99%

“…Case (ii): Δ(t) is in the multiplicative form For this case, the matrix parameters ,  , and  (t) are considered based on the multiplicative norm-bounded condition (8) and the free parameters 𝜆 1 , 𝜆 2 , 𝜆 3 , , and  are selected as in the Case (i). The feasibility of LMIs (11), (12), (34), and (35), in Theorem 2, can be easily checked with the aid of MATLAB-Yalmip toolbox, and correspondingly, the estimator gain and triggering matrices are calculated as  = . The initial data of the NNs (1) and its estimator (6) are considered as same in the previous case.…”

Section: Case (Ii): δ(T) Is In the Multiplicative Formmentioning

confidence: 99%

See 1 more Smart Citation

Event‐triggered nonfragile state estimation for delayed neural networks with additive and multiplicative gain variations

Karnan

Nagamani

2023

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

This article aims to design a nonfragile state estimator for neural networks with time-varying delay under the event-triggered mechanism. This paper addresses the two most common issues that exist in large-scale networks: gain variations in the estimator design and lack of network resources. Based on the nonfragile paradigm and an event-triggered mechanism, an estimator is being developed to address this issue, considering both the additive and multiplicative structured gain variations. Through the Lyapunov-Krasovskii functional method and linear matrix inequality technique, sufficient conditions are derived to guarantee the existence of the proposed state estimator by employing the generalized free-weighting matrix inequality and improved reciprocally convex inequality.Moreover, the obtained linear matrix inequalities provide an explicit expression of the estimator gain matrix and triggering matrix. Eventually, two numerical examples are provided to authenticate the proposed findings.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Case (Ii): δ(T) Is In the Multiplicative Formmentioning

confidence: 99%

Event‐triggered nonfragile state estimation for delayed neural networks with additive and multiplicative gain variations

Karnan

Nagamani

2023

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

show abstract

“…Besides that, the conventional T-S fuzzy control techniques can be applied to the chaotic systems. In [38,39], the free-weight matrix method and sampled-data control in [40] was connected to improve the productivity of fuzzy controlled in chaotic systems. In [41], the Lyapunov technique is used in the examination of T-S fuzzy chaotic systems via sampled-data control.…”

Section: Introductionmentioning

confidence: 99%

Exponential sampled‐data fuzzy stabilization of nonlinear systems and its application to basic buck converters

Gunasekaran

Zhai

2021

IET Control Theory & Appl

View full text Add to dashboard Cite

This study focuses on the exponential stability and stabilization of nonlinear systems via fuzzy sampled-data control technique. The stability and stabilization conditions are obtained through constructing suitable Lyapunov functional which contains the sampling information and the solvable linear matrix inequalities. Then, the dynamics of the nonlinear buck converter system and Lorenz system with the sampled-data controller is analyzed and designed. Finally, the proposed method is validated with a basic buck converter system model designed to reflect the characteristics of the power metal-oxide-semiconductor field-effect transistors in the numerical section. In addition, the superiority of the sufficient conditions obtained is shown by comparing with the existing methods of the Lorentz system. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

show abstract

Improved Stability Criteria for Discrete-time Delay Systems via Novel Summation Inequalities

Xiao

Zeng

et al. 2018

Int. J. Control Autom. Syst.

View full text Add to dashboard Cite

Free-matrix-based integral inequality for stability analysis of uncertain T-S fuzzy systems with time-varying delay

Cited by 6 publications

References 29 publications

Event‐triggered nonfragile state estimation for delayed neural networks with additive and multiplicative gain variations

Event‐triggered nonfragile state estimation for delayed neural networks with additive and multiplicative gain variations

Exponential sampled‐data fuzzy stabilization of nonlinear systems and its application to basic buck converters

Improved Stability Criteria for Discrete-time Delay Systems via Novel Summation Inequalities

Contact Info

Product

Resources

About