Research article

Stability analysis for time delay systems via a generalized double integral inequality

  • Received: 01 July 2020 Accepted: 11 August 2020 Published: 18 August 2020
  • MSC : 34D20, 34K20, 34K25

  • This paper proposes a new stability condition for a class of time delay systems. Firstly, a generalized double integral inequality is obtained. Then, a less conservative stability criterion is proposed by using the double integral inequality and choosing some new Lyapunov-Krasovskii functionals. Finally, two numerical examples are proposed to show the effectiveness of our method.

    Citation: Junkang Tian, Zerong Ren, Shouming Zhong. Stability analysis for time delay systems via a generalized double integral inequality[J]. AIMS Mathematics, 2020, 5(6): 6448-6456. doi: 10.3934/math.2020415

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  • This paper proposes a new stability condition for a class of time delay systems. Firstly, a generalized double integral inequality is obtained. Then, a less conservative stability criterion is proposed by using the double integral inequality and choosing some new Lyapunov-Krasovskii functionals. Finally, two numerical examples are proposed to show the effectiveness of our method.


    A time delay widely exists in many fields such as chemistry, biology, industry, and so on. Since a time delay arising in a system may cause instability, the stability analysis of time-delay systems has been wildly studied in the past few decades [1,2]. The main purpose is paid to determine the admissible delay, for which the systems remain stable.

    It is well known that the LKF method has been widely used to obtain stability conditions for time-delay systems [3,4]. The main purpose of the LKF method is to estimate the integral term arising in the time derivative of double integral term in the LKF. Therefore, to get less conservative stability criteria, many integral inequality methods are derived. Those inequality methods include Jensen inequality [5,6], Wirtinger inequality [7,8,9], double integral inequlity [10,11,12], various improved integral inequalities [13,14,15,16,17,18,19,20,21,22,23,24,25,26]. The Jensen inequality expressed as Vab(˙y)=ba˙yT(t)R˙y(t)dt1baΩT0RΩ0=VJensen, where a<b,R=RT>0,Ω0=y(b)y(a). The Wirtinger-based inequality expressed as Vab(˙y)VJensen+3baΩT1RΩ1=VSeuret, where Ω1=y(b)+y(a)2babay(t)dt. The further improved inequality expressed asVab(˙y)VSeuret+5baΩT2RΩ2, Vab(˙y)VSeuret+5baΩT2RΩ2+7baΩT3RΩ3, Vab(˙y)VSeuret+5baΩT2RΩ2+7baΩT3RΩ3+9baΩT4RΩ4 in [13,14,15], respectively, where Ω2,Ω3,Ω4 are defined in Lemma 4 [15]. However, these results only estimate the integral term arising in the time derivative of double integral term in the LKF. This paper presents a generalized double integral inequality which includes those in [10,11,12] as special cases. A new stability criterion is proposed by choosing a new LKF and using the generalized double integral inequality. Both the generalized integral inequality and the new LKF include fourth integrals, which may yield less conservative results. Two examples are introduced to show the effectiveness of the proposed criterion. The contributions of our paper are as follows:

    The integral babu˙xT(s)P˙x(s)dsdu is estimated asbabu˙xT(s)P˙x(s)dsduζTωζ, where ω and ζ are defined in Lemma 3. The above inequality includes those in [10,11,12] as special cases.

    Both the new double integral inequality and the new LKF include fourth integrals, which may obtain more general results.

    Notation: See Table 1.

    Table 1.  Nomenclature.
    Sn+ the set of n×n symmetric positive definite matrices
    Rm m-dimensional Euclidean space
    A The transpose of the A matrix
    Sym(P) P+P, For any square matrix P 
    0 A zero matrix with appropriate dimensions

     | Show Table
    DownLoad: CSV

    Consider the time delay systems as

    ˙y(t)=Ay(t)+By(th)+Ctthy(s)ds (2.1)
    y(t)=ϕ(t),t[h,0] (2.2)

    where y(t)Rn is the state vector, h>0 is constant time-delay and the initial condition ϕ(t) is a continuous function.

    Lemma 1. [15] For a matrix PSn+, and any continuously differentiable function x:[a,b]Rn, then we can obtain

    ba˙xT(s)P˙x(s)ds1ba4i=0(2i+1)ΩTiPΩi (2.3)

    where

    Ω0=x(b)x(a)
    Ω1=x(b)+x(a)2babax(t)dt
    Ω2=x(b)x(a)+6babax(t)dt12(ba)2babux(t)dtdu
    Ω3=x(b)+x(a)12babax(t)dt+60(ba)2babux(t)dtdu120(ba)3babubvx(t)dtdvdu
    Ω4=x(b)x(a)+20babax(t)dt180(ba)2babux(t)dtdu+840(ba)3babubvx(t)dtdvdu1680(ba)4babubvbβx(t)dtdβdvdu

    Lemma 2. [27] For a positive define matrix PSn+, a integrable function {x(s)|s[a,b]}, and any auxiliary functions {fi(s)|i[0,n],s[a,b],f0(s)=1} satisfying babufi(s)fj(s)dsdu=0, (0i,jn,ij) with fi(s)0,i=1,2,,n. Let λiRn×k,i=0,1,,n and a vector ζRk, such thatbabufi(s)x(s)dsdu=λiζ. Then for any matrices MiRk×n(i=0,1,,n), the following inequality holds

    babuxT(s)Px(s)dsduζT{ni=0babuf2i(s)dsduMiP1MTi+Sym(ni=0Miλi)}ζ (2.4)

    Proof. Define M=[MT0MT1MTn]T, ξ(s)=[f0(s)ζTf1(s)ζTfn(s)ζT]T.

    It is easy to obtain that

    2ξT(s)Mx(s)ξT(s)MP1Mξ(s)+xT(s)Px(s) (2.5)

    Integrating the inequality (2.5) from [a,b]×[u,b] yields

    2ζTni=0Mibabufi(s)x(s)dsduζT{ni=0babuf2i(s)dsduMiP1MTi+2ni=0nj=i+1babufi(s)fj(s)dsduMiP1MTi}ζ+babuxT(s)Px(s)dsdu=ζT{ni=0babuf2i(s)dsduMiP1MTi}ζ+babuxT(s)Px(s)dsdu (2.6)

    This completes the proof.

    Lemma 3. For a differential function x:[a,b]Rn, a matrix PRn+, a vector ζRk, and any matrices MiRk×n(i=1,2,3,4), then the following inequality holds:

    babu˙xT(s)P˙x(s)dsduζTωζ (2.7)

    where

    ω=(ba)22(M1P1MT1+12M2P1MT2+13M3P1MT3+14M4P1MT4)+(ba)Sym(M1λ1+M2λ2+M3λ3+M4λ4)
    λ1ζ=x(b)1babax(s)ds
    λ2ζ=x(b)+2babax(s)ds6(ba)2babux(s)dsddu
    λ3ζ=x(b)3babax(s)ds+24(ba)2babux(s)dsdu60(ba)3babubvx(s)dsdvdu
    λ4ζ=x(b)+4babax(s)ds60(ba)2babux(s)dsdu+360(ba)3babubvx(s)dsdvdu840(ba)4babubvbβx(s)dsdβdvdu

    Proof. The result can be easily obtained by choosing n=3, f1(s)=3ba(s2b+a3), f2(s)=10(ba)2[(s3b+2a5)23(ba)250], f3(s)=4+30saba60(saba)2+35(saba)3in (2.4). So the details of proof is omitted.

    Remark 1. The inequality (25) of Lemma 5.1 in [10] is a special case of Lemma 3 by setting M1=2baλT1R, M2=4baλT2R, M3=0, and M4=0. The inequality (4) of Lemma 2.3 in [11] is a special case of Lemma 3 by setting M1=2baλT1R, M2=4baλT2R, M3=6baλT3R, and M4=0. In addition, the inequality (12) of Lemma 5 in [12] is a special case of Lemma 3 by set ting M1=2baλT1R, M2=4baλT2R, M3=6baλT3R, and M4=8baλT4R.

    Based on Lemma 1 and Lemma 3, a new stability condition can be obtained.

    Theorem 1. System (1) is asymptotically stable if there exist matrices PS5n+, R1,R2,R3Sn+, and any matrices M1,M2,M3,M4R6n×n such that

    Ψ=Sym(ΠT1PΠ2)+δT1R1δ1δT2R1δ2+h2δT0R2δ0+h22δT0R3δ0ΠT3R2Π33ΠT4R2Π45ΠT5R2Π57ΠT6R2Π69ΠT7R2Π7+h22(M1R13MT1+12M2R13MT2+13M3R13MT3+14M4R14MT4)+hSym(M1Π8+M2Π9+M3Π10+M4Π11)<0 (3.1)

    where

    Π1=[δT1δT3δT4δT5δT6]T,

    Π2=[δT0δT1δT2hδT1δT3h22δT1δT4h36δT1δT5],

    Π3=δ1δ2,

    Π4=δ1+δ22hδ3,

    Π5=δ1δ2+6hδ312h2δ4,

    Π6=δ1+δ212hδ3+60h2δ4120h3δ5,

    Π7=δ1δ2+20hδ3180h2δ4+840h3δ51680h4δ6,

    Π8=δ11hδ3,

    Π9=δ1+2hδ36h2δ4,

    Π10=δ13hδ3+24h2δ460h3δ5,

    Π11=δ1+4hδ360h2δ4+360h3δ5840h4δ6,

    δ0=Aδ1+Bδ2+Cδ3,

    δi=[0n×(i1)nIn0n×(7i)n], i=1,2,,6.

    Proof. Introduce a LKF as

    V(yt)=ζT(t)Pζ(t)+tthyT(s)R1y(s)ds+htthtu˙yT(s)R2˙y(s)dsdu+tthtutv˙yT(s)R3˙y(s)dsdvdu (3.2)

    where

    ζ(t)=[yT(t)tthyT(s)dsvT1(t)vT2(t)vT3(t)]T

    vT1(t)=tthtu1yT(s)dsdu1

    vT2(t)=tthtu1tu2yT(s)dsdu2du1

    vT3(t)=tthtu1tu2tu3yT(s)dsdu3du2du1

    Then, the time derivative of V(yt) along the trajectories of system (1) as follows

    ˙V(yt)=2ζT(t)P˙ζ(t)+yT(t)R1y(t)yT(th)R1y(th)+h2˙yT(t)R2˙y(t)+h22˙yT(t)R3˙y(t)htth˙yT(s)R2˙y(s)dstthtu˙yT(s)R3˙y(s)dsdu=ηT(t){Sym(ΠT1PΠ2)+δT0Qδ0δT7Qδ7+δT1R1δ1δT2R1δ2+h2δT0R2δ0+h22δT0R3δ0}η(t)htth˙yT(s)R2˙y(s)dstthtu˙yT(s)R3˙y(s)dsdu (3.3)

    where

    η(t)=[yT(t)yT(th)tthyT(s)dsvT1(t)vT2(t)vT3(t)]T

    By Lemma 1, we have

    htth˙yT(s)R2˙y(s)dsηT(t)(ΠT3R2Π33ΠT4R2Π45ΠT5R2Π57ΠT6R2Π69ΠT7R2Π7)η(t) (3.4)

    By Lemma 3, we have

    tthtu˙yT(s)R3˙y(s)dsduηT(t)[h224i=11iMiR13MTi+hSym(4i=1MiΠi+7)]η(t) (3.5)

    Thus, according to (3.2)–(3.5), we have ˙V(yt)ηT(t)Ψη(t). Thus, if (3.1)holds, then, for a sufficient small scalar ε>0, ˙V(yt)εy(t)2 holds, which ensures system (1) is asymptotically stable. The proof is completed.

    Remark 2. Both the double integral inequality and the new LKF include fourth integrals, which may yield novel stability results. Furthermore, in order to fully consider relevant information of the double integral inequality in Lemma 3, the tthtu1tu2tu3yT(s)dsdu3du2du1 is added as a state vector.

    In this section, we demonstrate the advantages of our proposed criterion by two numerical examples.

    Example 1. Consider system(1) with:

    A=[0.200.20.1], B=[0000], C=[1011].

    Table 2 lists the allowable upper bounds of h by different methods. Table 2 shows that the maximum delay bounds of h obtained by our method are much larger than those in [4,6,7,9,11].

    Table 2.  Maximal bound h for Example 1.
    methods Maximal h NoDv
    [7] 1.877 16
    [9] 1.9504 59
    [4] 2.0395 75
    [6] 2.0395 27
    [11] 2.0402 45
    Theorem 1 2.0412 64

     | Show Table
    DownLoad: CSV

    Example 2. Consider system(1) with:

    A=[011001], B=[0.00.10.10.2], C=[0000]

    Table 3 lists the allowable upper bounds of h by different methods. Table 3 shows that the maximum delay bounds of h obtained by our method are much larger than those in [4,7,9,10,11,14]. For h=0.750, y(0)=(0.001,0.001)T, the state trajectories of the system(1) is given in Figure 1.

    Table 3.  Maximal bound h for Example 2.
    methods Maximal h NoDv
    [7] 0.126 16
    [9] 0.126 59
    [4] 0.577 75
    [10] 0.577 96
    [11] 0.675 45
    [14] 0.728 45
    Theorem 1 0.750 64

     | Show Table
    DownLoad: CSV
    Figure 1.  the state trajectories of the system(1) of example 2.

    Remark 3. According to Example 1 and Example 2, although our method can reduce the conservatism of the system effectively, it increases the computational burden.

    This paper focus on a new stability condition for a class of time delay systems. By using two generalized integral inequalities and a new augmented LKF, a new stability criterion is obtained. Both the double integral inequality and the new LKF include fourth integrals, which may yield more general results. Two numerical examples are proposed to show the effectiveness of the proposed criterion.

    This work was supported by New Academic Talents and Innovation Exploration Project of Department of Science and Technology of Guizhou Province of China under Grant (Qian ke he pingtai rencai [2017] 5727-19); Innovative Groups of Education Department of Guizhou Province (Qian jiao he KY [2016] 046).

    The authors declare that there are no conflicts of interest.



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