Loading [MathJax]/jax/output/SVG/jax.js
Research article

Further results on stability analysis of Takagi–Sugeno fuzzy time-delay systems via improved Lyapunov–Krasovskii functional

  • The problem of delay-range-dependent (DRD) stability analysis for continuous time Takagi–Sugeno (T–S) fuzzy time-delay systems (TDSs) is addressed in this paper. An improved DRD stability criterion is proposed in an linear matrix inequality (LMI) framework by constructing an appropriate delay-product-type (DPT) Lyapunov–Krasovskii functional (LKF) to make use of Bessel-Legendre polynomial based relaxed integral inequality. The modification in the proposed LKF along with the judicious choice of integral inequalities helps to obtain a less conservative delay upper bound for a given lower bound. The efficacy of the obtained stability conditions is validated through the solution of three numerical examples.

    Citation: Rupak Datta, Ramasamy Saravanakumar, Rajeeb Dey, Baby Bhattacharya. Further results on stability analysis of Takagi–Sugeno fuzzy time-delay systems via improved Lyapunov–Krasovskii functional[J]. AIMS Mathematics, 2022, 7(9): 16464-16481. doi: 10.3934/math.2022901

    Related Papers:

    [1] Marwa M. Tharwat, Marwa M. Ahmed, Ammara Nosheen, Khuram Ali Khan, Iram Shahzadi, Dumitru Baleanu, Ahmed A. El-Deeb . Dynamic inequalities of Grüss, Ostrowski and Trapezoid type via diamond-α integrals and Montgomery identity. AIMS Mathematics, 2024, 9(5): 12778-12799. doi: 10.3934/math.2024624
    [2] Andrea Aglić Aljinović, Domagoj Kovačević, Mehmet Kunt, Mate Puljiz . Correction: Quantum Montgomery identity and quantum estimates of Ostrowski type inequalities. AIMS Mathematics, 2021, 6(2): 1880-1888. doi: 10.3934/math.2021114
    [3] Mehmet Kunt, Artion Kashuri, Tingsong Du, Abdul Wakil Baidar . Quantum Montgomery identity and quantum estimates of Ostrowski type inequalities. AIMS Mathematics, 2020, 5(6): 5439-5457. doi: 10.3934/math.2020349
    [4] Hüseyin Budak, Ebru Pehlivan . Weighted Ostrowski, trapezoid and midpoint type inequalities for RiemannLiouville fractional integrals. AIMS Mathematics, 2020, 5(3): 1960-1984. doi: 10.3934/math.2020131
    [5] Erhan Set, Ahmet Ocak Akdemir, Abdurrahman Gözpınar, Fahd Jarad . Ostrowski type inequalities via new fractional conformable integrals. AIMS Mathematics, 2019, 4(6): 1684-1697. doi: 10.3934/math.2019.6.1684
    [6] Mustafa Gürbüz, Yakup Taşdan, Erhan Set . Ostrowski type inequalities via the Katugampola fractional integrals. AIMS Mathematics, 2020, 5(1): 42-53. doi: 10.3934/math.2020004
    [7] Serap Özcan, Saad Ihsan Butt, Sanja Tipurić-Spužević, Bandar Bin Mohsin . Construction of new fractional inequalities via generalized n-fractional polynomial s-type convexity. AIMS Mathematics, 2024, 9(9): 23924-23944. doi: 10.3934/math.20241163
    [8] Humaira Kalsoom, Muhammad Idrees, Artion Kashuri, Muhammad Uzair Awan, Yu-Ming Chu . Some New (p1p2,q1q2)-Estimates of Ostrowski-type integral inequalities via n-polynomials s-type convexity. AIMS Mathematics, 2020, 5(6): 7122-7144. doi: 10.3934/math.2020456
    [9] Anjum Mustafa Khan Abbasi, Matloob Anwar . Ostrowski type inequalities for exponentially s-convex functions on time scale. AIMS Mathematics, 2022, 7(3): 4700-4710. doi: 10.3934/math.2022261
    [10] Gültekin Tınaztepe, Sevda Sezer, Zeynep Eken, Sinem Sezer Evcan . The Ostrowski inequality for s-convex functions in the third sense. AIMS Mathematics, 2022, 7(4): 5605-5615. doi: 10.3934/math.2022310
  • The problem of delay-range-dependent (DRD) stability analysis for continuous time Takagi–Sugeno (T–S) fuzzy time-delay systems (TDSs) is addressed in this paper. An improved DRD stability criterion is proposed in an linear matrix inequality (LMI) framework by constructing an appropriate delay-product-type (DPT) Lyapunov–Krasovskii functional (LKF) to make use of Bessel-Legendre polynomial based relaxed integral inequality. The modification in the proposed LKF along with the judicious choice of integral inequalities helps to obtain a less conservative delay upper bound for a given lower bound. The efficacy of the obtained stability conditions is validated through the solution of three numerical examples.



    In 1938, A. M. Ostrowski introduced the subsequent appealing integral-based inequality to relate the value of a function Ψ with its integral from α to β:

    Consider Ψ:[α,β]R is continuous on [α,β] and differentiable in (α,β), such that Ψ:(α,β)R is bounded in (α,β), i.e. Ψ:=supˆa(α,β)|Ψ(ˆa)|<. Subsequently for any ˆa[α,β], we have:

    |(βα)Ψ(ˆa)βαΨ(s)ds|[(βα)24+(ˆaα+β2)2]Ψ. (1.1)

    If the fraction 14 cannot be substituted by any smaller value then it leads to sharpness of the above inequality.

    Afterward, several researchers have brought in few findings through the extensions and generalizations of Inequality (1.1). Such inequalities can be employed to guesstimate the inaccuracy of approximation in integration while investigating the steadiness and consistency of statistical calculation [1].

    Stefan Hilger [2] developed the calculus of measure chains in 1988. His Ph.D. supervisor Bernd Aulbach described core contributions of this theory of Unification, Extension and Discretization. The concept of time scales is a novelty in applied sciences as well as in mathematics as it enlightens a number of indefinite points about differential equations and solutions of some fractional order differential equations, which have been proved to be inadequate for their solution. Additionally, it has enlarged its contribution to the literature with its applications in areas such as engineering, biostatistics, mathematical biology, functional spaces, optimization theory and dynamic inequalities. The theory of time scales has attracted a great attention of researchers for resolving many problems in analysis. Some dynamical inequalities on time scales can be found in [3,4,5], where researchers established convex function-based inequalities, new Hardy-type inequalities and inequalities for product of different kinds of convex functions respectively using various analytical and theoretical approach on time scales. Furthermore Hu & Wang [6] discussed dynamic inequalities on time scales with applications in permanence of predator-prey system and Saker [7] employed some dynamic inequalities of Opial-type on time scales to prove numerous results related to the spacing between successive zeros of a solution of a second order dynamic equation with a damping term. Bohner and Matthews ([8,Theorem 3.5]) characterized the following relation on Γ as a generalization of the Ostrowski Inequality (1.1) :

    Let α,β,ˆu,ˆvΓ,α<β, and Ψ:[α,β]Γ=[α,β]ΓR is differentiable. Then we have the inequality:

    |Ψ(ˆv)1βαβαΨσ(ˆu)Δ(ˆu)|Mβα(Ω2(ˆv,α)+Ω2(ˆv,β)),

    where M=supα<ˆv<β|ΨΔ(ˆv)|< and [α,β]Γ is a closed interval under Γ. If its R.H.S of Inequality (1.1) cannot be substituted by any smaller value then it leads to sharpness of the above inequality.

    Liu & Ngô ([9,Lemma 3.2]) proved the following identity: Let α,β,ˆu,ˆvΓ,α<β and Ψ:[α,β]ΓR is differentiable. Then the following relation for all η[0,1] holds.

    (1η)Ψ(ˆv)+ηΨ(α)+Ψ(β)2=1βαβαΨσ(ˆu)Δˆu+1βαβαK(ˆv,ˆu)ΨΔ(ˆv)Δˆu, (1.2)

    where,

    K(ˆu,ˆv)={ˆuα+ηβα2,ˆu[α,ˆv),ˆuβηβα2,ˆu[ˆv,β].

    By making use of (1.2), they have expanded the Inequality (1.1) by considering parameter η and developed the following Ostrowski type inequality involving parameter η ([9,Theorem 3.1]):

    Let α,β,ˆu,ˆvΓ,α<β, and that Ψ:[α,β]ΓR is differentiable function. Then the following relation holds true:

    |(1η)Ψ(ˆv)+ηΨ(α)+Ψ(β)21βαβαΨσ(ˆu)Δˆu|Mβα[Ω2(α,α+ηβα2)+Ω2(ˆv,α+ηβα2)+Ω2(ˆv,βηβα2)+Ω2(β,βηβα2)] (1.3)

    for all η[0,1], such that α+ηβα2 and βηβα2 are in Γ where ˆv[α+ηβα2,βηβα2]Γ, and M=supα<ˆv<β|ΨΔ(ˆv)|<. Its sharpness is conditioned with

    η2α(βα)+η24(βα)2α+ηβα2αˆuΔˆu.

    Here [α,β]Γ represents a closed interval on Γ.

    Xu & Fang [10,Lemma 1] investigated the following identity: Let α,β,ˆu,ˆvΓ,α<β,Ψ:[α,β]ΓR is differentiable, and ζ:[0,1][0,1] is given, then we have

    Hζ(η)2Ψ(ˆv)+ζ(η)Ψ(α)+GΨ(β)2=1βαβαΨσ(ˆu)Δˆu+1βαβαK(ˆu,ˆv)ΨΔ(ˆu)Δˆu, (1.4)

    where

    K(ˆu,ˆv)={ˆuα1,ˆu[α,ˆv),ˆuα2,ˆu[ˆv,β].

    By making use of (1.4), they proved Ostrowski Inequality [10,Theorem 1] by using a parametric function and developed the result:

    Let α,β,ˆu,ˆvΓ,α<β,Ψ:[α,β]ΓR is differentiable, and ζ:[0,1][0,1], then

    |Gζ(η)2Ψ(ˆv)+ζ(η)Ψ(α)+HΨ(β)21βββαΨΔ(ˆu)Δˆu|Mβα(Ω2(α,α1)+Ω2(ˆv,α1)+Ω2(ˆv,α2)+Ω2(β,α2)) (1.5)

    for all η[0,1] such that α1 and α2 are in Γ, and t[α1,α2]Γ, where M=supα<ˆv<β|ΨΔ(ˆv)|<. Its sharpness is conditioned with

    ζ2(η)2ζ(η)2αζ2(η)2βαα1ˆuΔˆu.

    We refer [11,12,13] for detail textual-cum-mathematical description on the weighted Ostrowski type inequalities (wOTIs) via time scales. Such as Liu, Tuna and Jiang [11] developed few wOTIs by using weighted Montgomery identity on Γ. Liu and Tuna [13] characterized wOTIs on Γ by utilizing the concept of combined dynamic derivatives on Γ. Several scholars investigated multivariate OTIs on Γ in [14,15,16]. Few authors [17,18,19,20,21,22,23,24,25,26,27,28] utilized various methods to develop OTIs on Γ for functions of two variables. Motivated by the mentioned work, we extend OTIs for bivariate functions, which can be considered as generalizations of OTIs proved by Liu & Ngô, Xu & Fang and by Dragomir et al. [29].

    (1) Time scale: It is a closed subset of the real numbers. In present study, it is denoted by the symbol Γ. Examples of time scales include Cantor set, closed intervals, Z.

    (2) Forward jump operator: For tΓ, the Forward jump operator ρ:ΓΓ is defined as

    σ(ˆv):=inf{ˆuΓ:ˆu>ˆv}.

    (3) Γk notation:

    Γk={Γ(ρ(supΓ),supΓ],supΓ<,Γ,supΓ=.

    (4) Ψσ notation: If Ψ:ΓR is a function, then we define a function Ψσ:ΓR by

    Ψσ(ˆv)=Ψ(σ(ˆv)),ˆvΓ,

    i.e., Ψσ=Ψσ.

    (5) rd-continuous function: A function ζ:ΓR is stated as rd-continuous if it is continuous and its left-sided limits exist at right-dense points and left dense points respectively in Γ. The symbol Crd stands for the family of all such functions.

    (6) The delta derivative: Let Ψ:ΓR with ˆvΓk. The term ΨΔ(ˆv) is said to be a number (if exists) if for any ϵ>0, a neighbourhood U of ˆv (i.e., U=(ˆvδ,ˆv+δ)Γ for any δ>0) such that

    |[Ψ(σ(ˆv))Ψ(ˆu)]ΨΔ(ˆv)[σ(ˆv)ˆu]|ε|σ(ˆv)ˆu|forallˆuU.

    The value ΨΔ(ˆv) is known as the delta (or Hilger) derivative of Ψ at ˆv. Furthermore, the function Ψ is said to be delta differentiable on Γk if ΨΔ(ˆv) exists ˆvΓk.

    (7) Integration by parts: If α,βΓ and Ψ,ζCrd then

    βαΨ(σ(ˆv))ζΔ(ˆv)Δˆv=(Ψζ)(β)(Ψζ)(α)βαΨΔ(ˆv)ζ(ˆv)Δˆv, (1.6)

    or

    βαΨ(ˆv)ζΔ(ˆv)Δˆv=(Ψζ)(β)(Ψζ)(α)βαΨΔ(ˆv)ζ(σ(ˆv))Δˆv. (1.7)

    (8) Polynomials on time scales: The generalized polynomials are the functions ζk,Ωk:Γ2R,kN0, defined recursively as follow: the functions Ω0 and ζ0 are ζ0(ˆv,ˆu)=Ω0(ˆv,ˆu)=1 for all ˆu,ˆvΓ, and, for given ζk and Ωk with kN0, the functions ζk+1 and Ωk+1 are ζk+1(ˆv,ˆu)=ˆvˆuζk(σ(τ),ˆu)Δτ, for all ˆu,ˆvΓ and Ωk+1(ˆv,ˆu)=ˆvˆuΩk(τ,ˆu)Δτ for all ˆu,ˆvΓ. If ΩΔk(ˆv,ˆu) represents the derivative of Ωk(ˆv,ˆu) w.r.t. ˆv for any ˆu, then ΩΔk(ˆv,ˆu)=Ωk1(ˆv,ˆu),kN,ˆvΓk. Similarly ζΔk(ˆv,ˆu)=ζk1(σ(ˆv),ˆu)kN,ˆvΓk.

    For further study of time scale calculus, readers are referred to [30,31].

    Note: In this article, several abbreviations are used in order to lighten the notation and shorten the proofs; we refer to the table at the end just after the section of conclusions. Moreover throughout the paper we consider [a,b]Γ=[a,b]Γ.

    This section presents the characterization of novel wOTIs on Γ through the generalization of Montgomery identity with parameter functions.

    Lemma 2.1. Let α,β,γ,θ,ˆu,ˆvΓ with α<β,γ<θ,Ψ:I=[α,β]Γ1×[γ,θ]Γ2R is differentiable. Assume that the delta derivatives ΨΔΔ(ˆv,ˆu) exist on I and ζ:[0,1][0,1]. Then we have the following identity

    {Jθγ2}βαΨσ(ˆv,ˆy)Δˆv +{ζ(η)θγ2}βαΨσ(ˆv,γ)Δˆv+{Hθγ2}βαΨσ(ˆv,θ)Δˆv+βαk1(ˆx,ˆv){θγΨΔσ(ˆv,ˆu)Δˆu}Δˆv+βαθγk1(ˆx,ˆv)k2(ˆy,ˆu)ΨΔΔ(ˆv,ˆu)ΔˆuΔˆv={J2.(θγ)(βα)4}Ψ(ˆx,ˆy)+{ζ(η)J(θγ)(βα)4}{Ψ(α,ˆy)+Ψ(ˆx,γ)}+{HJ.(θγ)(βα)4}{Ψ(β,ˆy)+Ψ(ˆx,θ)}+{ζ2(η).(θγ)(βα)4}Ψ(α,γ)+{ζ(η)H.(θγ)(βα)4}{Ψ(β,γ)+Ψ(α,θ)}+{H2.(θγ)(βα)4}Ψ(β,θ), (2.1)

    where

    k1(ˆx,ˆv)={ˆvα1,ˆv[α,ˆx);ˆvα2,ˆv[ˆx,β],&k2(ˆy,ˆu)={ˆuγ1,ˆu[γ,ˆy);ˆuγ2,ˆu[ˆy,θ].

    Proof. Since

    βαθγk1(ˆx,ˆv)k2(ˆy,ˆu)ΨΔΔ(ˆv,ˆu)ΔˆuΔˆv=βαk1(ˆx,ˆv)[θγk2(ˆy,ˆu)ΨΔΔ(ˆv,ˆu)Δˆu]Δˆv. (2.2)

    Denote

    I1=θγk2(ˆy,ˆu)ΨΔΔ(ˆv,ˆu)Δˆu=ˆyγ[ˆuγ1]ΨΔΔ(ˆv,ˆu)Δˆu+θˆy[ˆuγ2]ΨΔΔ(ˆv,ˆu)ΔˆuI2+I3. (2.3)

    By using (1.6), we integrate I2 to get

    I2=[ˆyγ1]ΨΔ(ˆv,ˆy)+ζ(η)θγ2)ΨΔ(ˆv,γ)ˆyγΨΔσ(ˆv,ˆu)Δˆu.

    Similarly

    I3=[θγ2]ΨΔ(ˆv,θ)[ˆyγ2]ΨΔ(ˆv,ˆy)θˆyΨΔσ(ˆv,ˆu)Δˆu.

    By using I2 and I3 in (2.3), we have

    I1=[ˆyγζ(η)θγ2ˆy+γ+Gθγ2]ΨΔ(ˆv,ˆy)+ζ(η)θγ2)ΨΔ(ˆv,γ)+[{2H}θγ2]ΨΔ(ˆv,θ)θγΨΔσ(ˆv,ˆu)Δˆu=[Jθγ2]ΨΔ(ˆv,ˆy)+ζ(η)θγ2)ΨΔ(ˆv,γ)+[Hθγ2]ΨΔ(ˆv,θ)θγΨΔσ(ˆv,ˆu)Δˆu.

    Use I1 in (2.2) to find

    βαθγk1(ˆx,ˆv)k2(ˆy,ˆu)ΨΔΔ(ˆv,ˆu)ΔˆuΔˆv=[Jθγ2]I4+{ζ(η)θγ2}I5+[Hθγ2]I6βαk1(ˆx,ˆv){θγΨΔσ(ˆv,ˆu)Δˆu}Δˆv, (2.4)

    where I4=βαk1(ˆx,ˆv)ΨΔ(ˆv,ˆy)Δˆv, I5=βαk1(ˆx,ˆv)ΨΔ(ˆv,γ)Δˆv and I6=βαk1(ˆx,ˆv)ΨΔ(ˆv,θ)Δˆv.

    Now,

    I4=ˆxα[ˆvα1]ΨΔ(ˆv,ˆy)Δˆv+βˆx[ˆvα2]ΨΔ(ˆv,ˆy)ΔˆvI7+I8. (2.5)

    Use (1.6) to find

    I7={ˆxα1}Ψ(ˆx,ˆy)+ζ(η)βα2)Ψ(α,ˆy)ˆxαΨσ(ˆv,ˆy)Δˆv.

    In similar fashion,

    I8={Hβα2}Ψ(β,ˆy){ˆxα2}Ψ(ˆx,ˆy)βˆxΨσ(ˆv,ˆy)Δˆv.

    By adding I7 and I8, we have

    I4=[{J}βα2]Ψ(ˆx,ˆy)+{ζ(η)βα2}Ψ(α,ˆy)+{Hβα2}Ψ(β,ˆy)βαΨσ(ˆv,ˆy)Δˆv.

    Similar calculations for I5 and I6 give

    I5=[{J}βα2]Ψ(ˆx,γ)+{ζ(η)βα2}Ψ(α,γ)+{Hβα2}Ψ(β,γ)βαΨσ(ˆv,γ)Δˆv

    and

    I6={Jβα2}Ψ(ˆx,θ)+{ζ(η)βα2}Ψ(α,θ)+{Hβα2}Ψ(β,θ)βαΨσ(ˆv,θ)Δˆv.

    Using I4, I5 and I6 in (2.4), we have

    βαθγk1(ˆx,ˆv)k2(ˆy,ˆu)ΨΔΔ(ˆv,ˆu)ΔˆuΔˆv=[Jθγ2][{Jβα2}Ψ(ˆx,ˆy)+{ζ(η)βα2}Ψ(α,ˆy)+{Hβα2}Ψ(β,ˆy)βαΨσ(ˆv,ˆy)Δˆv}]+{ζ(η)θγ2}[{Jβα2}Ψ(ˆx,γ)+{ζ(η)βα2}Ψ(α,γ)+{Hβα2}Ψ(β,γ)βαΨσ(ˆv,γ)Δˆv]+[Hθγ2][{(1ζ(η)+ζ(1η))βα2}Ψ(ˆx,θ)+ζ(η)βα2Ψ(α,θ)+{Hβα2}Ψ(β,θ)βαΨσ(ˆv,θ)Δˆv]βαk1(ˆx,ˆv){θγΨΔσ(ˆv,ˆu)Δˆu}Δˆv.

    Simplification yields

    {Jθγ2}βαΨσ(ˆv,ˆy)Δˆv+{ζ(η)θγ2}βαΨσ(ˆv,γ)Δˆv+{Hθγ2}βαΨσ(ˆv,θ)Δˆv+βαk1(ˆx,ˆv){θγΨΔσ(ˆv,ˆu)Δˆu}Δˆv+βαθγk1(ˆx,ˆv)k2(ˆy,ˆu)ΨΔΔ(ˆv,ˆu)ΔˆuΔˆv={J2.(θγ)(βα)4}Ψ(ˆx,ˆy)+{ζ(η)J(θγ)(βα)4}{Ψ(α,ˆy)+Ψ(ˆx,γ)}+{HJ.(θγ)(βα)4}{Ψ(β,ˆy)+Ψ(ˆx,θ)}+{ζ2(η).(θγ)(βα)4}Ψ(α,γ)+{ζ(η)H.(θγ)(βα)4}{Ψ(β,γ)+Ψ(α,θ)}+{H2.(θγ)(βα)4}Ψ(β,θ).

    Remark 2.1. If Ψ is single valued function then Eq (2.1) coincides with [10,Lemma 1].

    Corollary 2.1. Let α,β,γ,θ,ˆu,ˆvΓ with α<β,γ<θ,Ψ:I=[α,β]Γ1×[γ,θ]Γ2R is differentiable. Assume that the delta derivatives ΨΔΔ(ˆv,ˆu) exist on I and η[0,1]. We then have the equation

    {(1η)2(θγ)(βα)}Ψ(ˆx,ˆy)+{η(1η)(θγ)βα2}[Ψ(α,ˆy)+Ψ(β,ˆy)+Ψ(ˆx,γ)+Ψ(ˆx,θ)]+{η2.(θγ)(βα)4}[Ψ(α,γ)+Ψ(β,γ)+Ψ(α,θ)+Ψ(β,θ)]=(θγ)βαΨσ(ˆv,θ)Δˆv+βαk1(ˆx,ˆv)[θγΨΔσ(ˆv,ˆu)Δˆu]Δˆv+βαθγk1(ˆx,ˆv)k2(ˆy,ˆu)ΨΔΔ(ˆv,ˆu)ΔˆuΔˆv, (2.6)

    where

    k1(ˆx,ˆv)={ˆv(α+(η)βα2),ˆv[α,ˆx),ˆv(α+(2η)βα2),ˆv[ˆx,β],k2(ˆy,ˆu)={ˆu(γ+(η)θγ2),ˆu[γ,ˆy),ˆu(γ+(2η)θγ2),ˆu[ˆy,θ].

    Proof. If we choose ζ(η)=η in Lemma 2.1, we get the required estimate.

    Remark 2.2. If Ψ is single valued function then Eq (2.6) coincides with [9,Lemma 3.2].

    Theorem 2.1. Suppose that α,β,γ,θ,ˆu,ˆvΓ with α<β,γ<θ,Ψ:I=[α,β]Γ1×[γ,θ]Γ2R is differentiable. Assume that the delta derivatives ΨΔΔ(ˆv,ˆu) exist on I and ζ:[0,1][0,1]. We then have the inequality

    |J2Ψ(ˆx,ˆy)+ζ(η)J{Ψ(α,ˆy)+Ψ(ˆx,γ)}+HJ{Ψ(β,ˆy)+Ψ(ˆx,θ)}+ζ2(η)Ψ(α,γ)+ζ(η)H{Ψ(β,γ)+Ψ(α,θ)}+{H2Ψ(β,θ){J2βα}βαΨσ(ˆv,ˆy)Δˆv}{ζ(η)2βα}βαΨσ(ˆv,γ)Δˆv{H2βα}βαΨσ(ˆv,θ)Δˆv|4M(βα)(θγ)H2(α,β,ˆx,α1,α2)((θγ)+H2(γ,θ,ˆy,γ1,γ2)), (2.7)

    for all η[0,1] such that α1 and α2 are in Γ1, and ˆx[α,β]Γ1, γ1 and γ2 are in Γ2, ˆy[γ,θ]Γ2, where M1=Supα<ˆv<βγ<ˆu<θ|ΨΔΔ(ˆv,ˆu)|<, M2=Supα<ˆv<βγ<ˆu<θ|ΨΔσ(ˆv,ˆu)|< and M:=Max{M1,M2}.

    Proof. By taking absolute value on both sides of (2.1), one yields

    |J2Ψ(ˆx,ˆy)+ζ(η)J{Ψ(α,ˆy)+Ψ(ˆx,γ)}+HJ{Ψ(β,ˆy)+Ψ(ˆx,θ)}+ζ2(η)Ψ(α,γ)+ζ(η)H{Ψ(β,γ)+Ψ(α,θ)}+{H2Ψ(β,θ){J2βα}βαΨσ(ˆv,ˆy)Δˆv}{ζ(η)2βα}βαΨσ(ˆv,γ)Δˆv{H2βα}βαΨσ(ˆv,θ)Δˆv|=4(βα)(θγ)|βαk1(ˆx,ˆv){θγΨΔσ(ˆv,ˆu)Δˆu}Δˆv+βαθγk1(ˆx,ˆv)k2(ˆy,ˆu)ΨΔΔ(ˆv,ˆu)ΔˆuΔˆv|.

    Further we have to use |Ψ+ζ||Ψ|+|ζ|, |βαΨdˆx|βα|Ψ|dˆx & |ΨΔσ(ˆv,ˆu)|M;|ΨΔΔ(ˆv,ˆu)|M;|Ψ.ζ|=|Ψ||ζ| toestimate as following:

    |J2Ψ(ˆx,ˆy)+ζ(η)J{Ψ(α,ˆy)+Ψ(ˆx,γ)}+HJ{Ψ(β,ˆy)+Ψ(ˆx,θ)}+ζ2(η)Ψ(α,γ)+ζ(η)H{Ψ(β,γ)+Ψ(α,θ)}+{H2Ψ(β,θ){J2βα}βαΨσ(ˆv,ˆy)Δˆv}{ζ(η)2βα}βαΨσ(ˆv,γ)Δˆv{H2βα}βαΨσ(ˆv,θ)Δˆv|4M(βα)(θγ)((θγ){ˆxα|k1(ˆx,ˆv)|Δˆv+βˆx|k1(ˆx,ˆv)|Δˆv}+βα|k1(ˆx,ˆv)|{ˆyγ|k2(ˆy,ˆu)|Δˆu+θˆy|k2(ˆy,ˆu)|Δˆu}Δˆv)4M(βα)(θγ)((θγ)H2(α,β,x,α1,α2)+βα|k1(ˆx,ˆv)|H2(γ,θ,y,γ1,γ2)Δˆv).

    Simplifications give the required result.

    Corollary 2.2. If all the assumptions of Corollary 2.1 hold, then we find the following Ostrowski type inequality for parameter η

    |4(1η)2Ψ(ˆx,ˆy)+2η(1η)[Ψ(α,ˆy)+Ψ(β,ˆy)+Ψ(ˆx,γ)+Ψ(ˆx,θ)]+η2[Ψ(α,γ)+Ψ(β,γ)+Ψ(α,θ)+Ψ(β,θ)]4βαβαΨσ(ˆv,θ)Δˆv|4M(βα)(θγ)(Ω2(α,α+ηβα2)+Ω2(ˆx,α+ηβα2)+Ω2(ˆx,α+(2η)βα2)+Ω2(β,α+(2η)βα2))((θγ)+Ω2(γ,γ+ηθγ2)+Ω2(ˆy,γ+ηθγ2)+Ω2(ˆy,γ+(2η)θγ2)+Ω2(θ,(γ+(2η)θγ2)). (2.8)

    Proof. The proof is similar to proof of Theorem 2.1.

    Remark 2.3. The inequality (2.8) can be considered as extension of [9,Theorem 3.1]. Since if Ψ is single valued in (2.8), we get [9,Theorem 3.1].

    Corollary 2.3. Under the assumptions of Theorem 2.1, we have the following Ostrowski type inequality:

    |4(1η)2Ψ(ˆx,ˆy)+2η2(1η){Ψ(α,ˆy)+Ψ(ˆx,γ)}+2η(2η)(1η){Ψ(β,ˆy)+Ψ(ˆx,θ)}+η4Ψ(α,γ)+η3(2η){Ψ(β,γ)+Ψ(α,θ)}+η2(2η)2Ψ(β,θ)4βαβα{Ψσ(ˆv,ˆy)+Ψσ(ˆv,γ)+Ψσ(ˆv,θ)}Δˆv|4M(βα)(θγ)(Ω2(α,α+η2βα2)+Ω2(ˆx,α+η2βα2)+Ω2(ˆx,α+(1+(1η)2)βα2)+Ω2(β,α+(1+(1η)2)βα2))((θγ)+Ω2(γ,γ+η2θγ2)+Ω2(ˆy,γ+η2θγ2)+Ω2(ˆy,γ+(1+(1η)2)θγ2)+Ω2(θ,(γ+(1+(1η)2)θγ2)). (2.9)

    Proof. Take ζ(η)=η2 in Theorem 2.1 to meet the requirement.

    Remark 2.4. The following Ostrowski type inequalities are obtained by choosing η=0,η=12 and η=1 in Corollary 2.3 respectively:

    (a) |Ψ(ˆx,ˆy)1βαβα{Ψσ(ˆv,ˆy)+Ψσ(ˆv,γ)+Ψσ(ˆv,θ)}Δˆv| M(βα)(θγ){Ω2(ˆx,α)+Ω2(ˆx,β)}[(θγ)+Ω2(ˆy,γ)+Ω2(ˆy,θ)].

    (b) |Ψ(ˆx,ˆy)+14{Ψ(α,ˆy)+Ψ(ˆx,γ)}+34{Ψ(β,ˆy)+Ψ(ˆx,θ)}+116Ψ(α,γ)+316{Ψ(β,γ)+Ψ(α,θ)}+916Ψ(β,θ)4βαβα{Ψσ(ˆv,ˆy)+Ψσ(ˆv,γ)+Ψσ(ˆv,θ)}Δˆv|4M(βα)(θγ)

    (Ω2(α,7α+β8)+Ω2(ˆx,7α+β8)+Ω2(ˆx,3α+5β8)+Ω2(β,3α+5β8))((θγ)+Ω2(γ,7γ+θ8)+Ω2(ˆy,7γ+θ8)+Ω2(ˆy,3γ+5θ8)+Ω2(θ,3γ+5θ8)).

    (c) |Ψ(α,γ)+Ψ(β,γ)+Ψ(α,θ)+Ψ(β,θ)4βαβα{Ψσ(ˆv,ˆy)+Ψσ(ˆv,γ)+Ψσ(ˆv,θ)}Δˆv|4M(βα)(θγ)

    (Ω2(α,α+β2)+Ω2(ˆx,α+β2)+Ω2(ˆx,α+β2)+Ω2(β,α+β2))((θγ)+Ω2(γ,γ+θ2)+Ω2(ˆy,γ+θ2)+Ω2(ˆy,γ+θ2)+Ω2(θ,γ+θ2)).

    Lemma 2.2. Let α,β,γ,θ,ˆu,ˆvΓ with α<β,γ<θ,Ψ:I=[α,β]Γ1×[γ,θ]Γ2R is differentiable. Assume that the delta derivatives ΨΔΔ(ˆv,ˆu) exist on I and ζ1,ζ2:[0,1][0,1]. We then have the equation

    (J1.J2)Ψ(ˆx,ˆy)+(ζ1(η)J2)Ψ(α,ˆy)+(J2.H1)Ψ(β,ˆy)+(ζ2(μ).J1)Ψ(ˆx,γ)+(ζ1(η).ζ2(μ))Ψ(α,γ)+(ζ2(μ)H1)Ψ(β,γ)+(H2J1)Ψ(ˆx,θ)+(ζ1(η)H2)Ψ(α,θ)+(H1H2)Ψ(β,θ)(J22βα).βαΨσ(ˆv,ˆy)Δˆv(ζ2(μ)2βα).βαΨσ(ˆv,γ)Δˆv(H22βα)βαΨσ(ˆv,θ)Δˆv=4(βα)(θγ)[βαk1(ˆx,ˆv)(θγΨΔσ(ˆv,ˆu)Δˆu)Δˆv+βαθγk1(ˆx,ˆv)k2(ˆy,ˆu)ΨΔΔ(ˆv,ˆu)ΔˆuΔˆv], (2.10)

    where

    k1(ˆx,ˆv)={ˆve1,ˆv[α,ˆx);ˆve2,ˆv[ˆx,β].k2(ˆy,ˆu)={ˆue3,ˆu[γ,ˆy);ˆue4,ˆu[ˆy,θ].

    Proof. It can easily be proved by following the steps of Lemma 2.1.

    Remark 2.5. If ζ1(η) = ζ2(μ) in Lemma 2.2, it becomes Lemma 2.1.

    Theorem 2.2. Suppose that α,β,γ,θ,ˆu,ˆvΓ with α<β,γ<θ,Ψ:I=[α,β]Γ1×[γ,θ]Γ2R is differentiable. Assume that the delta derivatives ΨΔΔ(ˆv,ˆu) exist on I and ζ1,ζ2:[0,1][0,1]. We then have the inequality

    |{J1.J2}Ψ(ˆx,ˆy)+{ζ1(η)J2}Ψ(α,ˆy)+{J2.H1}Ψ(β,ˆy)+{ζ2(μ).J1}Ψ(ˆx,γ)+{ζ1(η).ζ2(μ)}Ψ(α,γ)+{ζ2(μ)H1}Ψ(β,γ)+{H2J1}Ψ(ˆx,θ)+{ζ1(η)H2}Ψ(α,θ)+{H1H2}Ψ(β,θ){(1ζ2(μ)+ζ2(1μ))2βα}βαΨσ(ˆv,ˆy)Δˆv}{ζ2(μ)2βα}βαΨσ(ˆv,γ)Δˆv{H22βα}βαΨσ(ˆv,θ)Δˆv|4M(βα)(θγ)H2(α,β,x,e1,e2)((θγ)+H2(γ,θ,y,e3,e4)). (2.11)

    Proof. By using Lemma 2.2 and adopting the technique of proof of Theorem 2.1, we get the desired result.

    Remark 2.6. In similar fashion, remaining results of Section 2.2 can be extended for (2.11).

    Some important examples of time scales include continuous time scale Γ=R (set of all real numbers, which gives rise to differential equations), discrete time scale Z (set of integers, which gives rise to difference equations) and quantum time Scale qN0,q>1. In this section we have discussed Ostrowski type Inequality (2.8) for these special time scales.

    Example 3.1. If we take Γ1=Γ2=R, then the delta integral is the usual Riemann integral i.e. βαΨσ(ˆv)Δˆv=βαΨ(ˆv)dˆv as σ(ˆv)=ˆv. In this case, the generalized polynomial Ω2 is

    Ω2(ˆv,ˆu)=(ˆvˆu)22forallˆu,ˆvR,

    which implies the following relations:

    Ω2(α,α+ηβα2)=(ααηβα2)22=η2(βα)28,
    Ω2(ˆx,α+ηβα2)=4(ˆxα)2+η2(βα)24η(ˆxα)(βα)8,
    Ω2(ˆx,α+(2η)βα2)=4(ˆxα)2+(2η)2(βα)24(ˆxα)(2η)(βα)8,
    Ω2(β,α+(2η)βα2)=(βα)2η28,
    Ω2(γ,γ+ηθγ2)=η2(θγ)28,
    Ω2(ˆy,γ+ηθγ2)=4(ˆyγ)2+η2(θγ)24η(ˆyγ)(θγ)8,
    Ω2(ˆy,γ+(2η)θγ2)=4(ˆyγ)2+(2η)2(θγ)24(ˆyγ)(2η)(θγ)8,
    Ω2(θ,γ+(2η)θγ2)=(θγ)2η28.

    The Eq (2.8) takes the following form

    |4(1η)2Ψ(ˆx,ˆy)+2η(1η)[Ψ(α,ˆy)+Ψ(β,ˆy)+Ψ(ˆx,γ)+Ψ(ˆx,θ)]+η2[Ψ(α,γ)+Ψ(β,γ)+Ψ(α,θ)+Ψ(β,θ)]4βαβαΨ(ˆv,θ)dˆv|M(βα)(θγ)((βα)2(η2η)+(αˆx)2+(βˆx)2)(2(θγ)+(θγ)2(η2η)+(γˆy)2+(θˆy)2). (3.1)

    Remark 3.1. If Ψ is single valued function then assumptions and calculations made in Example 3.1 coincide with [29,Theorem 2].

    Example 3.2. Using Γ1=Γ2=Z,α=0=γ,β=n,θ=m,s=j,t=i,Ψ(p,q)=ˆxpˆyq,p=k,q=l and Ψσ(p,q)=σ(ˆxpˆyq)=ˆxp+1ˆyq+1; βαΨσ(ˆv,θ)Δˆv=4nn1t=0ˆxt+1ˆym in Eq (2.8), with the known result

    Ω2(ˆv,ˆu)=(ˆvˆu)!2!(ˆvs2)!=(ˆvˆu)(ˆvs1)2=(ˆvˆu2),forallˆu,ˆvZ,

    we have

    |4(1η)2ˆxkˆyl+2η(1η)[ˆx0ˆyl+ˆxnˆyl+ˆxkˆy0+ˆxkˆym]+η2[ˆx0ˆy0+ˆxnˆy0+ˆx0ˆym+ˆxnˆym]4nn1i=0ˆxi+1ˆym|M4mn(n2(η2η+1)+2k(kn1)+n)(5m+4m2(η2η+1)+8l(lm1)).

    Example 3.3. If we take Γ1=Γ2=qN0,q>1,α=γ=qm,β=θ=qn,m<n,η=1 in Eq (2.8), we have

    |Ψ(qm,qm)+Ψ(qn,qm)+Ψ(qm,qn)+Ψ(qn,qn)4qnqmqnqmΨσ(ˆv,qn)Δˆv|M(qnqm)2.14(1+q)2((qmqn)(qm(2q)qn+1)+2(2ˆxqnqm)(2ˆxqn+1qm+1)+(qnqm)(qn(2q)qm+1))(4(qnqm)(1+q)+(qmqn)(qm(2q)qn+1)+2(2ˆyqnqm)(2ˆyqn+1qm+1)+(qnqm)(qn(2q)qm+1)).

    Remark 3.2. If Ψ is single valued then Example 3.1 to Example 3.3 coincide with [9,Corollaries 3.6–3.8]. Furthermore, it is also possible to reset Eq (2.7) instead of Eq (2.8) for these particular time scales, which will be extensions of [10,Corollary 1,2] in case of continuous and discrete time scales.

    In this study, a novel approach is employed for the establishment of Ostrowski type integral inequalities for double integrals via Montgomery identity under the setting of time scales calculus. In addition, certain generalizations are made for some weighted and parameterized functions. Moreover, some particular cases, applications and examples are discussed for some specific time scales. It is also worth mentioning that the results of the paper extend the results of [9,10,29]. Further extensions can be sought by the expansion of this proposed study for multiple integrals.

    Following notations have been used in the paper for vivid understanding of the concept:

    Notations Used For
    G 1+ζ(1η)
    H 1ζ(1η)
    J 1ζ(η)+ζ(1η)
    α1 α+ζ(η)βα2
    α2 α+Gβα2
    γ1 γ+ζ(η)θγ2
    γ2 γ+Gθγ2
    H2(α,β,x,α1,α2) Ω2(α,α1)+Ω2(ˆx,α1)+Ω2(ˆx,α2)+Ω2(β,α2)
    H2(γ,θ,y,γ1,γ2) Ω2(γ,γ1)+Ω2(ˆy,γ1)+Ω2(ˆy,γ2)+Ω2(θ,γ2)
    e1 α+ζ1(η)βα2
    e2 α+G1βα2
    e3 γ+ζ2(η)θγ2
    e4 γ+G2θγ2
    H2(α,β,x,e1,e2) Ω2(α,e1)+Ω2(ˆx,e1)+Ω2(ˆx,e2)+Ω2(β,e2)
    H2(γ,θ,y,e3,e4) Ω2(γ,e3)+Ω2(ˆy,e3)+Ω2(ˆy,e4)+Ω2(θ,e4)
    G1 1+ζ1(1η)
    G2 1+ζ2(1μ)
    H1 1ζ1(1η)
    H2 1ζ2(1μ)
    J1 1ζ1(η)+ζ1(1η)
    J2 1ζ2(μ)+ζ2(1μ).

     | Show Table
    DownLoad: CSV

    This research received funding support from the NSRF via the Program Management Unit for Human Resources and Institutional Development, Research and Innovation (grant number B05F640088).

    The authors declare that there is no conflict of interests regarding the publication of this paper.



    [1] H. K. Khalil, J. W. Grizzle, Nonlinear systems, Prentice Hall, New Jersey, 1996.
    [2] V. Djordjevic, L. Dubonjic, M. M. Morato, D. Prsic, V. Stojanovic, Sensor fault estimation for hydraulic servo actuator based on sliding mode observer, Math. Modell. Control, 2 (2022), 34–43. https://doi.org/10.3934/mmc.2022005 doi: 10.3934/mmc.2022005
    [3] T. Takagi, M. Sugeno, Fuzzy identification of systems and its applications to modeling and control, IEEE Trans. Syst. Man Cybern., 15 (1985), 116–132. https://doi.org/10.1109/TSMC.1985.6313399 doi: 10.1109/TSMC.1985.6313399
    [4] C. Ge, Y. Shi, J. H. Park, C. Hua, Robust H stabilization for T–S fuzzy systems with time-varying delays and memory sampled-data control, Appl. Math. Comput., 346 (2019), 500–512. https://doi.org/10.1016/j.amc.2018.10.076 doi: 10.1016/j.amc.2018.10.076
    [5] C. Peng, Q. L. Han, Delay-range-dependent robust stabilization for uncertain T–S fuzzy control systems with interval time-varying delays, Inf. Sci., 181 (2011), 4287–4299. https://doi.org/10.1016/j.ins.2011.05.025 doi: 10.1016/j.ins.2011.05.025
    [6] F. O. Souza, V. C. S. Campos, R. M. Palhares, On delay-dependent stability conditions for Takagi–Sugeno fuzzy systems, J. Frankl. Inst., 351 (2014), 3707–3718. https://doi.org/10.1016/j.jfranklin.2013.03.017 doi: 10.1016/j.jfranklin.2013.03.017
    [7] S. P. Boyd, L. El Ghaoui, E. Feron, V. Balakrishnan, Linear matrix inequalities in system and control theory, SIAM, Philadelphia, PA, 1994. https://doi.org/10.1137/1.9781611970777
    [8] K. Gu, V. L. Kharitonov, J. Chen, Stability of time-delay systems, MA: Birkhäuser, 2003. https://doi.org/10.1007/978-1-4612-0039-0
    [9] B. Jiang, Y. Lou, J. Lu, Input-to-state stability of delayed systems with bounded-delay impulses, Math. Modell. Control, 2, (2022), 44–54. https://doi.org/10.3934/mmc.2022006
    [10] E. Fridman, U. Shaked, An improved stabilization method for linear time-delay systems, IEEE Trans. Autom. Control, 47 (2002), 1931–1937. https://doi.org/10.1109/TAC.2002.804462 doi: 10.1109/TAC.2002.804462
    [11] Y. He, Q. G. Wang, L. Xie, C. Lin, Further improvement of free-weighting matrices technique for systems with time-varying delay, IEEE Trans. Autom. Control, 52 (2007), 293–299. https://doi.org/10.1109/TAC.2006.887907 doi: 10.1109/TAC.2006.887907
    [12] P. Park, J. W. Ko, C. Jeong, Reciprocally convex approach to stability of systems with time-varying delays, Automatica, 47 (2011), 235–238. https://doi.org/10.1016/j.automatica.2010.10.014 doi: 10.1016/j.automatica.2010.10.014
    [13] A. Seuret, F. Gouaisbaut, Wirtinger-based integral inequality: Application to time-delay systems, Automatica, 49 (2013), 2860–2866. https://doi.org/10.1016/j.automatica.2013.05.030 doi: 10.1016/j.automatica.2013.05.030
    [14] P. Park, W. I. Lee, S. Y. Lee, Auxiliary function-based integral inequalities for quadratic functions and their applications to time-delay systems, J. Frankl. Inst., 352 (2015), 1378–1396. https://doi.org/10.1016/j.jfranklin.2015.01.004 doi: 10.1016/j.jfranklin.2015.01.004
    [15] J. Chen, D. Xu, B. Shafai, On sufficient conditions for stability independent of delay, IEEE Trans. Autom. Control, 40 (1995), 1675–1680. https://doi.org/10.1109/9.412644 doi: 10.1109/9.412644
    [16] C. K. Zhang, F. Long, Y. He, W. Yao, L. Jiang, M. Wu, A relaxed quadratic function negative-determination lemma and its application to time-delay systems, Automatica, 113 (2020), 108764. https://doi.org/10.1016/j.automatica.2019.108764 doi: 10.1016/j.automatica.2019.108764
    [17] J. H. Kim, Further improvement of Jensen inequality and application to stability of time-delayed systems, Automatica, 64 (2016), 121–125. https://doi.org/10.1016/j.automatica.2015.08.025 doi: 10.1016/j.automatica.2015.08.025
    [18] F. S. de Oliveira, F. O. Souza, Further refinements in stability conditions for time-varying delay systems, Appl. Math. Comput., 369 (2020), 124866. https://doi.org/10.1016/j.amc.2019.124866 doi: 10.1016/j.amc.2019.124866
    [19] H. B. Zeng, H. C. Lin, Y. He, K. L. Teo, W. Wang, Hierarchical stability conditions for time-varying delay systems via an extended reciprocally convex quadratic inequality, J. Frankl. Inst., 357 (2020), 9930–9941. https://doi.org/10.1016/j.jfranklin.2020.07.034 doi: 10.1016/j.jfranklin.2020.07.034
    [20] Z. Feng, W. X. Zheng, Improved stability condition for Takagi–Sugeno fuzzy systems with time-varying delay, IEEE Trans. Cybern., 47 (2017), 661–670. https://doi.org/10.1109/TCYB.2016.2523544 doi: 10.1109/TCYB.2016.2523544
    [21] J. An, T. Li, G. Wen, R. Li, New stability conditions for uncertain T–S fuzzy systems with interval time-varying delay, Int. J. Control, Autom. Syst., 10 (2012), 490–497. https://doi.org/10.1007/s12555-012-0305-9 doi: 10.1007/s12555-012-0305-9
    [22] H. B. Zeng, J. H. Park, J. W. Xia, S. P. Xiao, Improved delay-dependent stability criteria for T–S fuzzy systems with time-varying delay, Appl. Math. Comput., 235 (2014), 492–501. https://doi.org/10.1016/j.amc.2014.03.005 doi: 10.1016/j.amc.2014.03.005
    [23] Z. Zhang, C. Lin, B. Chen, New stability and stabilization conditions for T–S fuzzy systems with time delay, Fuzzy Sets Syst., 263 (2015), 82–91. https://doi.org/10.1016/j.fss.2014.09.012 doi: 10.1016/j.fss.2014.09.012
    [24] R. Márquez, T. M. Guerra, A. Kruszewski, M. Bernal, Improvements on non-quadratic stabilization of Takagi–Sugeno models via line-integral Lyapunov functions, IFAC Proc. Vol., 46 (2013), 473–478. https://doi.org/10.3182/20130902-3-CN-3020.00165 doi: 10.3182/20130902-3-CN-3020.00165
    [25] C. Peng, L. Y. Wen, J. Q. Yang, On delay-dependent robust stability criteria for uncertain T–S fuzzy systems with interval time-varying delay, Int. J. Fuzzy Syst., 13 (2011), 35–44.
    [26] E. Tian, D. Yue, Y. Zhang, Delay-dependent robust H control for T–S fuzzy system with interval time-varying delay, Fuzzy Sets Syst., 160 (2009), 1708–1719. https://doi.org/10.1016/j.fss.2008.10.014 doi: 10.1016/j.fss.2008.10.014
    [27] Z. Lian, Y. He, C. K. Zhang, M. Wu, Stability analysis for T–S fuzzy systems with time-varying delay via free-matrix-based integral inequality, Int. J. Control Autom. Syst., 14 (2016), 21–28. https://doi.org/10.1007/s12555-015-2001-z doi: 10.1007/s12555-015-2001-z
    [28] F. Liu, M. Wu, Y. He, R. Yokoyama, New delay-dependent stability criteria for T–S fuzzy systems with time-varying delay, Fuzzy Sets Syst., 161 (2010), 2033–2042. https://doi.org/10.1016/j.fss.2009.12.014 doi: 10.1016/j.fss.2009.12.014
    [29] S. H. Tsai, Y. A. Chen, J. C. Lo, A novel stabilization condition for a class of T–S fuzzy time-delay systems, Neurocomputing, 175 (2016), 223–232. https://doi.org/10.1016/j.neucom.2015.10.054 doi: 10.1016/j.neucom.2015.10.054
    [30] R. Datta, R. Dey, B. Bhattacharya, A. Chakraborti, Improved stability condition for fuzzy systems with interval time varying delay, 2017 Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems (IFSA-SCIS), 2017, 1–6. https://doi.org/10.1109/IFSA-SCIS.2017.8023230
    [31] Z. Lian, Y. He, C. K. Zhang, M. Wu, Stability and stabilization of T–S fuzzy systems with time-varying delays via delay-product-type functional method, IEEE Trans. Cybern., 50 (2020), 2580–2589. https://doi.org/10.1109/TCYB.2018.2890425 doi: 10.1109/TCYB.2018.2890425
    [32] H. B. Zeng, J. H. Park, J. W. Xia, S. P. Xiao, Improved delay-dependent stability criteria for T–S fuzzy systems with time-varying delay, Appl. Math. Comput., 235 (2014), 492–501. https://doi.org/10.1016/j.amc.2014.03.005 doi: 10.1016/j.amc.2014.03.005
    [33] L. Huang, X. Xie, C. Tan, Improved stability criteria for T–S fuzzy systems with time-varying delay via convex analysis approach, IET Control Theory Appl., 10 (2016), 1888–1895. https://doi.org/10.1049/iet-cta.2015.1109 doi: 10.1049/iet-cta.2015.1109
    [34] Z. Lian, Y. He, C. K. Zhang, M. Wu, Further robust stability analysis for uncertain Takagi–Sugeno fuzzy systems with time-varying delay via relaxed integral inequality, Inf. Sci., 409 (2017), 139–150. https://doi.org/10.1016/j.ins.2017.05.017 doi: 10.1016/j.ins.2017.05.017
    [35] Z. Li, H. Yan, H. Zhang, J. Sun, H. K. Lam, Stability and stabilization with additive freedom for delayed Takagi–Sugeno fuzzy systems by intermediary polynomial-based functions, IEEE Trans. Fuzzy Syst., 28 (2019), 692–705. https://doi.org/10.1109/TFUZZ.2019.2914615 doi: 10.1109/TFUZZ.2019.2914615
    [36] X. J. Pan, B. Yang, J. J. Cao, X. D. Zhao, Improved stability analysis of Takagi–Sugeno fuzzy systems with time-varying delays via an extended delay-dependent reciprocally convex inequality, Inf. Sci., 571 (2021), 24–37. https://doi.org/10.1016/j.ins.2021.04.043 doi: 10.1016/j.ins.2021.04.043
    [37] O. M. Kwon, M. J. Park, J. H. Park, S. M. Lee, Stability and stabilization of T–S fuzzy systems with time-varying delays via augmented Lyapunov–Krasovskii functionals, Inf. Sci., 372 (2016), 1–15. https://doi.org/10.1016/j.ins.2016.08.026 doi: 10.1016/j.ins.2016.08.026
    [38] J. Tan, S. Dian, T. Zhao, Further studies on stability and stabilization of T–S fuzzy systems with time-varying delays via fuzzy Lyapunov–Krasovskii functional method, Asian J. Control, 20 (2018), 1–16. https://doi.org/10.1002/asjc.1697 doi: 10.1002/asjc.1697
    [39] R. Datta, R. Dey, B. Bhattacharya, R. Saravanakumar, O. M. Kwon, Stability and stabilization of T–S fuzzy systems with variable delays via new Bessel–Legendre polynomial based relaxed integral inequality, Inf. Sci., 522 (2020), 99–123. https://doi.org/10.1016/j.ins.2020.02.060 doi: 10.1016/j.ins.2020.02.060
    [40] R. Datta, R. Saravanakumar, R. Dey, B. Bhattacharya, C. K. Ahn, Improved stabilization criteria for Takagi–Sugeno fuzzy systems with variable delays, Inf. Sci., 579 (2021), 591–606. https://doi.org/10.1016/j.ins.2021.07.089 doi: 10.1016/j.ins.2021.07.089
    [41] X. Li, D. W. Ho, J. Cao, Finite-time stability and settling-time estimation of nonlinear impulsive systems, Automatica, 99 (2019), 361–368. https://doi.org/10.1016/j.automatica.2018.10.024 doi: 10.1016/j.automatica.2018.10.024
    [42] X. Li, S. Song, J. Wu, Exponential stability of nonlinear systems with delayed impulses and applications, IEEE Trans. Autom. Control, 64 (2019), 4024–4034. https://doi.org/10.1109/TAC.2019.2905271 doi: 10.1109/TAC.2019.2905271
    [43] X. Li, D. Peng, J. Cao, Lyapunov stability for impulsive systems via event-triggered impulsive control, IEEE Trans. Autom. Control, 65 (2020), 4908–4913. https://doi.org/10.1109/TAC.2020.2964558 doi: 10.1109/TAC.2020.2964558
    [44] Y. Zhang, X. Mu, Event-triggered output quantized control of discrete Markovian singular systems, Automatica, 135 (2022), 109992. https://doi.org/10.1016/j.automatica.2021.109992 doi: 10.1016/j.automatica.2021.109992
    [45] Y. Zhang, P. Shi, R. K. Agarwal, Y. Shi, Event-based mixed H and passive filtering for discrete singular stochastic systems, Int. J. Control, 93 (2020), 2407–2415. https://doi.org/10.1080/00207179.2018.1559360 doi: 10.1080/00207179.2018.1559360
    [46] Y. Zhang, P. Shi, R. K. Agarwal, Y. Shi, Event-based dissipative analysis for discrete time-delay singular jump neural networks, IEEE Trans. Neur. Net. Lear. Syst., 31 (2020), 1232–1241. https://doi.org/10.1109/TNNLS.2019.2919585 doi: 10.1109/TNNLS.2019.2919585
    [47] Y. Zhang, P. Shi, M. V. Basin, Event-based finite-time H filtering of discrete-time singular jump network systems, Int. J. Robust Nonlinear Control, 32 (2022), 4038–4054. https://doi.org/10.1002/rnc.6009 doi: 10.1002/rnc.6009
  • Reader Comments
  • © 2022 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(1929) PDF downloads(100) Cited by(1)

Figures and Tables

Figures(3)  /  Tables(3)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog