Research article

Adaptive constraint control for nonlinear multi-agent systems with undirected graphs

  • Received: 25 June 2021 Accepted: 12 August 2021 Published: 18 August 2021
  • MSC : 93B52, 93C42

  • This paper investigates the problem of adaptive distributed consensus control for stochastic multi-agent systems (MASs) with full state constraints. By utilizing adaptive backstepping control technique and barrier Lyapunov function (BLF), an adaptive distributed consensus constraint control method is proposed. The developed control method can ensure that all signals of the controlled system are semi-globally uniformly ultimately bounded (SGUUB) in probability, and outputs of the follower agents keep consensus with the output of leader. In addition, system states are not transgressed their constrained sets. Finally, simulation results are provided to illustrate the feasibility of the developed control algorithm and theorem.

    Citation: Lu Zhi, Jinxia Wu. Adaptive constraint control for nonlinear multi-agent systems with undirected graphs[J]. AIMS Mathematics, 2021, 6(11): 12051-12064. doi: 10.3934/math.2021698

    Related Papers:

    [1] Kaile Chen, Yunyun Liang, Nengqiu Zhang . Global existence of strong solutions to compressible Navier-Stokes-Korteweg equations with external potential force. AIMS Mathematics, 2023, 8(11): 27712-27724. doi: 10.3934/math.20231418
    [2] Yasir Nadeem Anjam . The qualitative analysis of solution of the Stokes and Navier-Stokes system in non-smooth domains with weighted Sobolev spaces. AIMS Mathematics, 2021, 6(6): 5647-5674. doi: 10.3934/math.2021334
    [3] Linlin Tan, Meiying Cui, Bianru Cheng . An approach to the global well-posedness of a coupled 3-dimensional Navier-Stokes-Darcy model with Beavers-Joseph-Saffman-Jones interface boundary condition. AIMS Mathematics, 2024, 9(3): 6993-7016. doi: 10.3934/math.2024341
    [4] Xiaoxia Wang, Jinping Jiang . The pullback attractor for the 2D g-Navier-Stokes equation with nonlinear damping and time delay. AIMS Mathematics, 2023, 8(11): 26650-26664. doi: 10.3934/math.20231363
    [5] Hui Fang, Yihan Fan, Yanping Zhou . Energy equality for the compressible Navier-Stokes-Korteweg equations. AIMS Mathematics, 2022, 7(4): 5808-5820. doi: 10.3934/math.2022321
    [6] Qingkun Xiao, Jianzhu Sun, Tong Tang . Uniform regularity of the isentropic Navier-Stokes-Maxwell system. AIMS Mathematics, 2022, 7(4): 6694-6701. doi: 10.3934/math.2022373
    [7] Jianxia He, Ming Li . Existence of global solution to 3D density-dependent incompressible Navier-Stokes equations. AIMS Mathematics, 2024, 9(3): 7728-7750. doi: 10.3934/math.2024375
    [8] Yasir Nadeem Anjam . Singularities and regularity of stationary Stokes and Navier-Stokes equations on polygonal domains and their treatments. AIMS Mathematics, 2020, 5(1): 440-466. doi: 10.3934/math.2020030
    [9] Jae-Myoung Kim . Time decay rates for the coupled modified Navier-Stokes and Maxwell equations on a half space. AIMS Mathematics, 2021, 6(12): 13423-13431. doi: 10.3934/math.2021777
    [10] Ning Duan, Xiaopeng Zhao . On global well-posedness to 3D Navier-Stokes-Landau-Lifshitz equations. AIMS Mathematics, 2020, 5(6): 6457-6463. doi: 10.3934/math.2020416
  • This paper investigates the problem of adaptive distributed consensus control for stochastic multi-agent systems (MASs) with full state constraints. By utilizing adaptive backstepping control technique and barrier Lyapunov function (BLF), an adaptive distributed consensus constraint control method is proposed. The developed control method can ensure that all signals of the controlled system are semi-globally uniformly ultimately bounded (SGUUB) in probability, and outputs of the follower agents keep consensus with the output of leader. In addition, system states are not transgressed their constrained sets. Finally, simulation results are provided to illustrate the feasibility of the developed control algorithm and theorem.



    The Navier-Stokes-Voigt (NSV) system models the dynamics of a Kelvin-Voigt viscoelastic incompresible fluid and its analysis was motivated by the studies carried out by Oskolkov in [32], where it is described a model of the motion of linear viscoelastic fluids (see, for instance, [22,33] and the references therein).

    The autonomous version of (NSV) system is given by:

    {t(uα2Δu)νΔ(u)+(u)(u)+p=f,in(0,+)×Ω,u=0,in(0,+)×Ω,u=0, on (0,+)×Ω,u(0,x)=u0(x),inΩ, (1.1)

    where Ω is a bounded domain in two or three-dimensional Euclidean space, u=(u1,u2,u3) is the unknown velocity field of the fluid and p is the unknown pressure, ν is the kinematic viscosity coefficient, α>0 is a length scale parameter which characterizes the elasticity of the fluid (in the sense that the ratio α2/ν describes the reaction time that is required for the fluid to respond to the applied force), u0 is the initial velocity field, and f is an external force term. Obviously when α=0, this system becomes the classical Navier-Stokes one.

    Recently, Navier-Stokes-Voigt systems have been proposed (see [4]) as regularizations of the 3D-Navier-Stokes equation for the purpose of direct numerical simulation (see also [1,2,3,14,21,23,31] for more details about NSV systems). In [4], some analytical studies of three-dimensional viscous and inviscid simplified Bardina turbulence models with periodic boundary conditions are carried out. In this paper, the authors prove the global well-posedness of this model for weaker initial conditions, establish an upper bound to the dimension of its global attractor and identify this dimension with the number of degrees of freedom for this model, and they establish the global existence and uniqueness of weak solutions to the inviscid model.

    In this autonomous framework, the long time behavior of (1.1) has been widely studied. For example, the existence of a compact global attractor is proved in Kalantarov [18], and Kalantarov and Titi [20] investigate the long-term dynamics of the three-dimensional Navier-Stokes-Voigt model of a viscoelastic incompressible fluid. Specifically, upper bounds for the number of determining modes are derived for the 3D Navier-Stokes-Voigt equations, and subsequently used to provide information about the dimension of its global attractor. From a numerical analysis point of view, the authors consider the Navier-Stokes-Voigt model as a non-viscous (inviscid) regularization of the three-dimensional Navier-Stokes equations. Furthermore, it is also shown that the weak solutions of the Navier-Stokes-Voight equations converge, in an appropriate norm, to the weak solutions of the inviscid simplified Bardina model, as the viscosity coefficient ν0.

    Other related results, which are worth being mentioned, are concerned with the Gévrey regularity of the global attractor when the force term is analytic of Gévrey type, and the establishment of similar statistical properties (and invariant measures) as for the 3D-Navier-Stokes equations (see [19,24,35] for more details).

    No doubt at all, the autonomous system (1.1) can be regarded as a simplification of a more realistic model of reality. It is well understood that a realistic model should take into account non-autonomous, stochastic or random effects. Also, it is very important to notice that delay or memory terms are determining the evolution of physical models. Indeed, it is sensible to think that in the future evolution of a system not only the current state has influence but also the past history of the phenomena. Moreover, when one is interested in controlling the problem by using some feedback control, the use of delay terms is fully required and justified. Due to some of these reasons, we will consider in this paper the following non-autonomous and delay version of system (1.1):

    {t(uα2Δu)νΔ(u)+(u)(u)+p=f(t)+g(t,ut),in(τ,+)×Ω,u=0,in(τ,+)×Ω,u=0, on (τ,+)×Ω,u(τ,x)=uτ(x),inΩ,u(τ+t,x)=ϕ(t,x),in(h,0)×Ω, (1.2)

    where ΩR3 is a bounded domain with smooth enough boundary (e.g., C2) Ω, τR is the initial time, uτ is an initial velocity field at the initial time τR, ϕ is a given function defined in the interval (h,0), and f is an external force term which may depend on time. Finally, the time-dependent delay term g(t,ut) represents, for instance, the influence of an external force with some kind of delay, memory or hereditary characteristics, although can also model some kind of feedback controls. Here, ut denotes a segment of the solution, in other words, given h>0 and a function u:[τh,+)×ΩR, for each tτ we define the mapping ut:[h,0]×ΩR by

    ut(θ,x)=u(t+θ,x), for θ[h,0],xΩ.

    In this way, this abstract formulation includes several types of delay terms in a unified way (as it is described in [9] and in the next sections).

    The non-autonomous case without delay (i.e., g=0) has been studied, for instance, in [40], where it is proved the asymptotic regularity of solutions as well as the existence of the uniform attractor, describing its structure and regularity. Luengo et al. [26] proved asymptotic compactness by using the energy method, and they further obtained the existence of pullback attractor for the three-dimensional non-autonomous NSV equations.

    Concerning the model with delays, the analysis was initiated by Caraballo and Real [9,10,11] in the case α=0 (i.e., the Navier-Stokes model) by establishing existence and eventual uniqueness of weak solutions, asymptotic behavior of the steady-state solutions, as well as the existence of pullback and uniform attractors (see also [5,16,27,30,34]). Later on, this analysis has been extended to other variants of Navier-Stokes systems such as the α-Navier-Stokes model ([7]), and the globally modified Navier-Stokes ([28,29]).

    The Navier-Stokes-Voigt equations with finite delays or with memory have been studied recently in [15,17,38] in some particular cases for the delay. In the first paper, the authors prove the existence of a uniform global attractor for a version containing some memory. In the second, the authors prove the well-posedness of the problem and the existence of pullback attractor when the term g contains variable delay, i.e., g(u(tρ(t))), with ρC1([0,+)), ρ(t)ρ0<1, and in [38], the model is two-dimensional and contains variable and distributed delay, g(t,ut)=g0(tρ(t),u(tρ(t))+0hG(s,u(t+s))ds, with ρC1([0,+)), ρ(t)M<1, and it is proved the existence of pullback attractor.

    It is remarkable that, to the best of our knowledge, none of the published papers in the literature considered the existence, eventual uniqueness, and asymptotic stability of the steady state solutions for system (1.2). This is a very important feature since, in order to obtain a detailed analysis of the geometric structure of global (and/or pullback) attractors, it is necessary to know about the existence of equilibria (steady-state solutions) and their asymptotic properties, since their associate unstable manifolds play a key role in determining the geometrical structure and complexity of the attractors. Motivated by these reasons, our main aim in this paper is to provide significant information on the asymptotic behavior of solutions for this model. We are interested in covering a wide variety of delay terms within a unified formulation. For this reason, we will analyze problem (1.2) which contains an abstract expression for the delay terms under the form of functional equations (say g(t,ut)). The presence of delays in the models implies the necessity of working in a quite different phase space, for instance, the initial values must be now initial functions which must belong to some appropriate spaces, and this fact implies that we have to work in more complicated functional spaces, for instance, in a Banach space of continuous functions, rather than in a Hilbert space.

    Consequently, our aim in this paper is to prove the well-posedness of system (1.2), prove the existence of stationary solutions and analyze their asymptotic behavior describing several methods which allow us to obtain different sufficient conditions. Since we will proceed with the abstract functional formulation for the delay term, our results generalize, in particular, some recent works obtained in the aforementioned literature for some particular cases of delay. This is, indeed, the main novelty of this paper, i.e., to set up a general enough framework which can include in a unified formulation most types of delay terms and carry out an analysis of the model in the sense of well-posedness of solutions and their asymptotic behavior. A more complete description of our contributions are included in the structure of our paper which is described in the next paragraph.

    The content of this paper is as follows. In Section 2 we set up the framework for our problem and include the necessary preliminaries. The existence, uniqueness and continuous dependence of solution on the initial data are proved in Section 3 by using a Galerkin approximation scheme and the energy equality. Finally, in Section 4 we first prove the existence of stationary (steady-state) solutions of our problem, and we next analyze the asymptotic behaviour of such stationary solutions, by establishing some sufficient conditions ensuring their exponential stability. We carry out our analysis by using three different techniques. We first use a Lyapunov function which, in the particular case of variable delay, requires differentiability of the delay function; next, we weaken this assumption to only continuity by using the Razumikhin technique; finally we exploit a technique based on a Gronwall-like inequality which works for general delay terms requiring only measurability assumptions. The analysis carried out in this paper is a first step for a more complete study of the asymptotic behavior of the problem including the existence and structure of attracting sets, which will be the topic of a future paper.

    Denote by (,) and ||, respectively, the scalar product and associate norm in (L2(Ω))3, and by (u,v) the scalar product in (L2(Ω))3×3 for the gradients of u and v.

    Let H be the closure in (L2(Ω))3 of the following set

    V={v(C0(Ω))3:v=0 in Ω},

    and let V be the closure of V in (H10(Ω))3. Then, H is a Hilbert space for the inner product of (L2(Ω))3, and V is a Hilbert subspace of (H10(Ω))3 with norm and inner product ((,)).

    We will use , to denote the duality product between V and V, and for the norm in V. It is well known that theses spaces satisfy VHV, where the injections are dense and compact.

    Denote by A the Stokes operator defined by

    Aw=P(Δw),wD(A), (2.1)

    where P is the Leray operator, i.e., is the projector operator from ((L2(Ω))3 onto H. Operator A is a linear continuous operator from V into V, satisfying

    Au,v=((u,v)), forall u,vV.

    Taking into account that Ω is regular enough, then D(A)=(H2(Ω))3V and |Aw| defines a norm in D(A) which is equivalent to the one in (H2(Ω))3, in other words, there exists a constant c1(Ω)>0 depending only on Ω such that

    w(H2(Ω))3c1(Ω)|Aw|,wD(A). (2.2)

    Consider now the trilinear form defined as

    b(u,v,w)=3i,j=1Ωuivjxiwjdx,

    for every function u,v,w:ΩR3 for which the right-hand side is well defined.

    In particular, b can be extended continuously to make sense for all u,v,wV, and is a continuous trilinear form on V×V×V, and satisfies

    |b(u,v,w)|C1uvw,u,v,wV, (2.3)
    b(u,v,w)=b(u,w,v),u,v,wV, (2.4)
    b(u,v,v)=0,u,vV, (2.5)

    and, using Agmon's inequality (e.g., cf [13]), we can assure that there exists a constant C2>0 such that

    |b(u,v,w)|C2|Au|1/2u1/2v|w|, (2.6)

    for all (u,v,w)D(A)×V×H.

    On the other hand, for any uV, we will use B(u) to denote the element of V given by

    B(u),w=b(u,u,w),wV.

    It follows from (2.3) that

    B(u)C1u2,uV, (2.7)

    and, in particular, by (2.6) and the identification of H with H, if uD(A), then B(u)H, with

    |B(u)|C2|Au|1/2u3/2,uD(A). (2.8)

    We now describe the assumptions on f,g and the initial values uτ and ϕ, for our model (1.2), and we recall the concept of variational solution.

    Let Y be a Banach space, and denote CY=C([h,0];Y) and L2Y=L2(h,0;Y).

    Assume g:R×CV (H1(Ω))3, satisfying:

    (H1) For all fixed ξCV, g(,ξ) is measurable,

    (H2) g(t,0)=0,tR,

    (H3) There exists Lg>0 such that for all tτ and ξ,μCV,

    ||g(t,ξ)g(t,μ)||(H1(Ω))3LgξμCV,

    (H4) There exist m10 and Cg>0 such that, for all m[0,m1],τt<T and u,v C0([τh,T];V),

    tτems||g(s,us)g(s,vs)||2(H1(Ω))3dsC2gtτhems||u(s)v(s)||2ds.

    Remark 2.1. In addition, notice that (H1)(H4) imply that, given u C([τh,T];V), the functional

    gu:t[τ,T](H1(Ω))3

    defined by gu(t)=g(t,ut) for all t[τ,T], is measurable and the mapping

    G:uC([τh,T];V)guL2(τ,T;(H1(Ω))3)

    possesses a unique extension to a mapping ˜G which is uniformly continuous from L2(τh,T;V) into L2(τ,T;(H1(Ω))3). From now on, we will denote g(t,ut)=˜G(u)(t) for any uL2(τh,T;V), and thus τt<T,u,vL2(τh,T;V), condition (H4) also holds.

    Assume fL2loc(R;(H1(Ω))3), uτV, ϕL2V.

    Definition 2.2. It is said that u is a weak solution to (1.2) if uL2(τh,T;V)L(τ,T;V) for all T>τ, and satisfies

    ddt(u(t)+α2Au(t))+νAu(t)+B(u(t))=f(t)+g(t,ut),inD(τ,;V), (2.9)

    and u(τ+t)=ϕ(t) for t(h,0), u(τ)=uτ.

    In this section we prove existence and uniqueness of solution for (1.2). But, before studying (1.2), we will analyse the autonomous equation u+α2Au=˜f. From the Lax-Milgram lemma, we deduce that for each ˜fV there exists a unique u˜fV such that

    u˜f+α2Au˜f=˜f. (3.1)

    The mapping F:uVu+α2AuV is linear and bijective, with F1˜f=u˜f. From (3.1), one has |u˜f|2+α2u˜f2˜fu˜f, and in particular, u˜fα2˜f, i.e.,

    F1˜fα2˜f,˜fV. (3.2)

    Observe that, by the definition of D(A), we also have that F1(H)=D(A), and reasoning as for the obtention of (3.2), we deduce that

    |Au˜f|=α2|˜fu˜f|2α2|˜f|,˜fH. (3.3)

    Remark 3.1. If uL2(τ,T;V) for all T>τ and satisfies (2.9), then the function v defined by

    v(t)=u(t)+α2Au(t),t>τ, (3.4)

    belongs to L2(τ,T;V) for all T>τ.

    On the other hand, by (H2) and (H4) we have

    tτ||g(s,us)||2VdsC2gtτh||u(s)||2ds=C2gττh||ϕ(sτ)||2ds+C2gtτ||u(s)||2ds, (3.5)

    and thanks to (2.7) and (3.5), we deduce that vL1(τ,T;V) for all T>τ.

    Consequently, vC([τ,+);V), and therefore, by (3.2), uC([τ,+);V). Moreover, again by (2.7), (2.9) and (3.5), vL2(τ,T;V) for all T>τ, and therefore, as u=F1v, we deduce that uL2(τ,T;V) for all T>τ.

    From previous considerations, it is clear that u is a weak solution to (1.2) if and only if uC([τ,+);V),uL2(τ,T;V) for all T>τ, and

    u(t)+α2Au(t)+tτ(νAu(s)+B(u(s)))ds=uτ+α2Auτ+tτf(s)ds+tτg(s,us)ds (equality in V), (3.6)

    for all tτ.

    Remark 3.2. Let u be a weak solution of (1.2). Then, u satisfies the energy equality:

    |u(t)|2+α2u(t)2+2νtsu(r)2dr=|u(s)|2+α2u(s)2+2tsf(r),u(r)dr+2tsg(r,ur),u(r)drs,t[τ,).

    Our main result in this section is the following.

    Theorem 3.3. Assume that g satisfies assumptions (H1)–(H4) and the following convergence one:

    (H5) For all T>0 and for any sequence {vn()}n1L2(h,T;V) such that vnv weakly in L2(h,T;V) and vnv strongly in L2(h,T;H), it follows that g(s,vns)g(s,vs) weakly in L2(0,T;(H1(Ω))3).

    Then, for each τR, uτV and ϕL2V, there exists a unique weak solution u=u(;τ,uτ,ϕ) of (1.2). Moreover, if uτD(A) and fL2loc(R;H), then uC([τ,);D(A)) and uL2(τ,T;D(A)), for all T>τ, and

    12ddt(u(t)2+α2|Au(t)|2)+ν|Au(t)|2+(B(u(t)),Au(t))=(f(t)+g(t,ut),Au(t)), a.e. t>τ. (3.7)

    Proof. For simplicity, we will argue in the case τ=0. The general case is similar. We split the proof of existence into three steps.

    A Galerkin scheme. First a priori estimates. Let us consider {vj}V, the orthonormal basis of H of all the eigenfunctions of the operator A (Avj=λjvj)). Denote Vm= span[v1,,vm] and consider the projector Pmu=mj=1(u,vj)vj.

    Define also

    um(t)=mj=1γm,j(t)vj,

    where the upper script m will be used instead of (m) since no confusion is possible with powers of u, and where the coefficients γm,j are required to satisfy the following system of ordinary differential equations:

    ddt(um(t)+α2Aum(t),vj)+νAum(t)+B(um(t)),vj=f(t),vj+g(t,umt),vj,a.e. t>0,1jm, (3.8)

    and the initial condition um(s)=Pmϕ(s) for s[h,0].

    Thanks to an appropriate modification of the Picard Theorem (see [9, Appendix]), the above system of ordinary functional differential Eq (3.8) possesses a unique local solution defined in [0,tm), with 0<tm.

    We prove now that the solutions do exist for all time t[0,+).

    Multiplying (3.8) by γm,j(t) and summing in j, and taking into account the properties of the operator b, we obtain for a.e. t0,

    12ddt(|um(t)|2+α2um(t)2)+νum(t)2=f(t)+g(t,umt),um(t), (3.9)

    and therefore, using Young's inequality, and taking into account (3.5),

    |um(t)|2+α2um(t)2|u0|2+α2u02+C2g0h||ϕ(s)||2ds+t0||f(s)||2(H1(Ω))3ds+(2+C2g)t0||um(s)||2ds,a.e. t(0,T). (3.10)

    From the above inequality and the Gronwall Lemma, the sequence {um} is bounded in L2(0,T;V) and in L(0,T;V), for any T>0.

    Now observe that by (3.8), if we denote vm=Fum, then vm satisfies

    ddt(vm(t))=˜Pm(νAum(t)B(um(t))+f(t)+g(t,ut)),a.e. t>0, (3.11)

    where

    ˜Pmg,w=g,PmwgV,wV.

    Consequently, as ˜PmL(V)1 for all m1, we deduce that the sequence {dvm/dt}m1 is bounded in L2(0,T;V) for all T>0, and therefore, taking into account that dum/dt=F1(dvm/dt), we have that the sequence {dum/dt}m1 is bounded in L2(0,T;V) for all T>0.

    Then, since the injection of V into H is compact, the Ascoli-Arzelà theorem implies that there exist a subsequence {um}m1 (we relabel the same) and a function uW1,2(0,T;V) for all T>0 with u=ϕ in (h,0), such that

    {umu weakly-star in L(0,T;V),umu weakly in L2(0,T;V),umu strongly in C([0,T];H),umu a.e. in Ω×(0,T),dumdtdudt weakly in L2(0,T;V),dvmdt=F(dumdt)F(dudt) weakly in L2(0,T;V), (3.12)

    for all T>0.

    Thanks to the properties of operator A and (3.12), we obtain that AumAu weakly in L2(0,T;V) for all T>0. Reasoning as in [25], Chapter 1, Lemma 1.3, we deduce that BumBu weakly in L2(0,T;V), for all T>0.

    On the other hand, thanks to assumption (H5), the convergences in (3.12) and the definition of ϕm, we deduce that

    g(t,umt)g(t,ut)in  L2(0,T;V).

    From all the convergences above, and (3.11), we can take limits and we prove that u is a global solution of (1.2) in the sense of Definition 2.2.

    Regularity. Assume now that u0D(A) and fL2loc(R;H).

    Multiplying in (3.8) by λjγm,j(t), and summing from j=1 to j=m, we obtain that a.e. t>0,

    ddt(um(t)2+α2|Aum(t)|2)+2ν|Aum(t)|2+2(B(um(t)),Aum(t))=2(f(t)+g(t,umt),Aum(t)). (3.13)

    But by (2.8) and the Young inequality,

    2|(B(um(t)),Aum(t))|Cνum(t)6+ν|Aum(t)|2,

    where Cν=27C42(16ν3)1.

    Also,

    2|(f(t),Aum(t))|ν2|Aum(t)|2+2ν1|f(t)|2.

    and

    2|(g(t,umt),Aum(t))|ν2|Aum(t)|2+2ν1|g(t,umt)|2.

    Observing that |APmu0||Au0| and Pmu0u0, from (3.13) we deduce in particular that

    α2|Aum(t)|2u02+α2|Au0|2+2ν1t0|f(s)|2ds+2ν1t0|g(s,ums)|2ds+Cνtsups[0,t]um(s)6, (3.14)

    for all t0, and any m1.

    Consequently, as {um}m1 is bounded in C([0,T];V), from (3.5) and (3.14), we have that {um}m1 is bounded in C([0,T];D(A)), for all T>0, and therefore, extracting a subsequence weakly-star convergent in L(0,T;D(A)), we see that uL(0,T;D(A)), for all T>0.

    But then, v=u+α2AuL(0,T;H), with v=νAuB(u)+f(t)+g(t,ut)L2(0,T;H), for all T>0, and therefore, vC([0,);H).

    Thus, Au=α2(vu)C([0,);H), i.e., uC([0,);D(A)).

    Moreover, as vL2(0,T;H), by (3.3), then u=F1vL2(0,T;D(A)), for all T>0.

    Identity (3.7). If u0D(A) and fL2loc(R;H), we have seen that uW1,2(0,T;D(A)) and v=FuW1,2(0,T;H), for all T>0. Then,

    ddt|v(t)|2=2(v(t),v(t)),a.e. t>0

    and taking into account that F is self-adjoint and that v(t)=Fu(t), we have

    ddt(u(t),v(t))=2(u(t),v(t)),a.e. t>0.

    Thus,

    ddt(Au(t),v(t))=α2ddt(v(t)u(t),v(t))=2(v(t),Au(t)),a.e. t>0.

    From this identity, taking into account (2.5) and (2.9), we have (3.7).

    Uniqueness. Let u(1) and u(2) be two weak solutions to (1.2), corresponding to the same data u0 and ϕ. Let us denote ˆu=u(1)u(2). It is obvious that ˆu(0,x)=0 in Ω and ˆu(t,x)=0 in (h,0)×Ω.

    From Definition (2.2) is easy to deduce that ˆu satisfies the following equality

    |ˆu(t)|2+α2ˆu(t)2+2νt0||ˆu(s)||2ds+2t0B(u1(s))B(u2(s)),ˆu(s)ds=2t0g(s,u1s)g(s,u2s),ˆu(s)ds, (3.15)

    for all t>0. But, on the one hand, by (2.3) we have that,

    B(u(1)(s))B(u(2)(s))=supwV,w=1|b(u(1)(s)u(2)(s),u(1)(s),w)b(u(2)(s),u(2)(s)u(1)(s),w)|C1(u(1)(s)+u(2)(s))u(1)(s)u(2)(s).

    Thus, if we fix an arbitrary T>0, and denote RT=C1maxs[0,T](u(1)(s)+u(2)(s)), we have

    B(u(1)(s))B(u(2)(s))RTu(1)(s)u(2)(s)for all s[0,T]. (3.16)

    On the other hand, by (H3) we deduce that

    2t0g(s,u1s)g(s,u2s),ˆu(s)ds2t0g(s,u1s)g(s,u2s)ˆu(s)ds2(t0g(s,u1s)g(s,u2s)2ds)1/2(t0ˆu(s)2ds)1/22Cg(thu1(s)u2(s)2ds)1/2(t0ˆu(s)2ds)1/2=2Cgt0ˆu(s)2ds (3.17)

    Then, as Aˆu(s)=ˆu(s), from (3.15), (3.16) and (3.17) we deduce that

    ˆu(t)α2(ν+RT+2Cg)t0ˆu(s)dsfor all t[0,T].

    From this inequality and Gronwall's lemma, we deduce that ˆu(t)=0 for all t[0,T], and therefore, the uniqueness of weak solution to (1.2).

    Remark 3.4. We emphasize that assumption (H5) does not need to be assumed if the delay term g:R×CH H, and satisfies:

    (H1) For all fixed ξCH, g(,ξ) is measurable$,

    (H2) g(t,0)=0,tR,

    (H3) There exists Lg>0 such that for all tτ and ξ,μCH,

    |g(t,ξ)g(t,μ)|LgξμCH,

    (H4) There exist m10 and Cg>0 such that, for all m[0,m1],τt<T and u,v C0([τh,T];H),

    tτems|g(s,us)g(s,vs)|2dsC2gtτhems|u(s)v(s)|2ds.

    See [9] for more details.

    We can also obtain a result on the continuous dependence on the initial data.

    Lemma 3.5. Let (uτ,ϕ),(vτ,ψ)V×L2V be two pairs of initial values for the problem (1.2), and τR an initial time. Denote by u()=u(;τ,(uτ,ϕ)) and v()=v(;τ,(vτ,ψ)) their corresponding associated solutions to (1.2). Then,

    u(t)v(t)2((1+λ11α2)uτvτ2+α2C2gνϕψ2L2V)×                                ×exp(tτ(α2C2gν+α2C21νv(s)2)ds),tτ. (3.18)

    As a consequence, it also follows

    utvt2CV((1+λ11α2)uτvτ2+α2C2gνϕψ2L2V)×                               ×exp(tτ(α2C2gν+α2C21νv(s)2)ds),tτ+h. (3.19)

    Proof. From (3.6) we obtain

    u(t)v(t)+α2A(u(t)v(t))+νtτA(u(s)v(s))ds   +tτ(B(u(s))B(v(s)))ds   =uτvτ+α2A(uτvτ)+tτ(g(s,us)g(s,vs))ds,t[τ,T].

    Denoting w=uv, we have

    12ddt(|w(t)|2+α2w(t)2)+νw(t)2+B(u(t))B(v(t)),w(t)=g(t,ut)g(t,vt),w(t). (3.20)

    Thanks to (2.3) and (2.5), we have

    |B(u(t))B(v(t)),w(t)|=|b(w(t),(v(t),w(t)|C1w(t)v(t)w(t)
    C212νw(t)2v(t)2+ν2w(t)2

    and then, from (3.20), we easily deduce

    ddt(|w(t)|2+α2w(t)2)C21νv(t)2w(t)2+1νg(t,ut)g(t,vt)2.

    Now, (H4) implies, for tτ,

    w(t)2w(τ)2α2C21νtτv(s)2w(s)2ds+α2C2gνtτhu(s)v(s)2ds+α2|w(τ)|2=λ1α2w(τ)2+α2C2gνϕψ2L2V+tτ(α2C2gν+α2C21νv(s)2)w(s)2ds.

    Thus,

    w(t)2(1+λ1α2)uτvτ2+α2C2gνϕψ2L2V+tτ(α2C2gν+α2C21νv(s)2)w(s)2ds, tτ,

    and, (3.18) holds by applying the Gronwall lemma. Finally, (3.19) is a straightforward consequence of (3.18).

    In this section we prove that, under additional hypotheses, there exists a unique stationary solution to problem (1.2) and it is globally asymptotically exponentially stable.

    From now on we assume that f(t)=f(H1(Ω))3 for all tτ, a constant function, and that g:R×CV (H1(Ω))3 satisfies (H1)–(H4), but is autonomous, in the sense that there exists a function g0:V(H1(Ω))3 such that

    g(t,w)=g0(w), for all (t,w)[τ,)×V,

    where, with a slight abuse of notation, we identify every element wV with the constant function in CV which is equal to w for any time t[h,0].

    Two examples, which can be considered as canonical within this situation are the following:

    (Forcing term with variable delay) Let G:R3 R3 be a measurable function satisfying G(0)=0, and assume that there exists M>0 such that

    |G(u)G(v)|R3M|uv|R3,u,vR3.

    Now, consider a function ρ(t), which is going to play the role of the delay. Assume that ρ() is measurable and define g(t,ξ)(x)=G(ξ(ρ(t))(x)) for each ξCV, xΩ and t[0,T]. In this case, the delayed term g in our problem becomes

    g(t,ut)=G(u(tρ(t))).

    (Forcing term with distributed delay) Let G:[h,0] ×R3 R3 be a measurable function satisfying G(s,0)=0 for all s[h,0], and there exists a function βL2(h,0) such that

    |G(s,u)G(s,v)|R3β(s)|uv|R3,u,vR3,s[h,0].

    Then, g is given by

    g(t,ξ)(x)=0hG(s,ξ(s)(x)) ds

    for each ξCV, t[0,T], xΩ, and the delayed term in our problem becomes

    g(t,ut)(x)=0hG(s,u(t+s)) ds

    Observe that both situations are within our framework, and hypothesis (H1)–(H4) are fulfilled under appropriate assumptions on the variable delay (see [9] for more details). In fact, these two examples are within the particular case mentioned in Remark 3.4. Therefore, we can ensure the existence and uniqueness of solutions of our model because (H5) is automatically fulfilled.

    We consider the following equation,

    ddt(u+α2Au)+νAu+B(u)=f+g(t,ut)t>τ. (4.1)

    A stationary (steady-state) solution to (4.1) is an element uV such that

    νAu,v+B(u),v=f,v+g0(u),vvV. (4.2)

    Now we recall a result ensuring existence of steady-state solutions for Eq (4.1) which, obviously, is the same as for the Navier-Stokes case considered in [6].

    Theorem 4.1. Under the above conditions, if ν>Lg, then:

    (a) Problem (4.1) admits at least one stationary solution u, which indeed belongs to D(A). Moreover, any stationary solution satisfies the estimate

    (νLg)uf(H1(Ω))3. (4.3)

    (b) If the following condition holds,

    2C1f(H1(Ω))3<(νLg)2, (4.4)

    then the stationary solution of (4.1) is unique.

    Proof. In [6] the authors prove an analogous result to the 2D-Navier-Stokes models, but the proof of the existence is valid for any dimension, while the uniqueness can be ensured for dimension less than or equal to 4 (see [39]). Therefore, we omit the proof of this theorem.

    Now, we will prove the existence and uniqueness of stationary solution, u, and that every weak solution approaches u exponentially.

    Theorem 4.2. Assume that assumptions in Theorem 3.3 and Theorem 4.1 hold true. Moreover, assume that ν>max{Cg,Lg} and

    C1f(H1(Ω))3<(νCg)(νLg). (4.5)

    Then, there exists λ>0 such that for the solution u(,0,u0,ϕ) of (1.2) with τ=0 and ϕL2V, the following estimate holds for all t0:

    |u(t,0,u0,ϕ)u|2eλt(|u0u|2+α2u0u2+Cgϕu2L2V), (4.6)

    where u is the unique stationary solution of (4.1) given by Theorem 4.1.

    Proof. Let us denote w(t)=u(t)u. Considering equations (4.1) for u(t) and (4.2) for u, one has

    ddt(w(t)+α2Aw(t),v)+ν((w(t),v))+B(u(t),vB(u,v=g(t,ut)g(u),v,

    for t>0, for any vV.

    Now, pick λ(0,m1) to be fixed later. Then

    ddt(eλt(|w(t)|2+α2w(t)2)) =λeλt(|w(t)|2+α2w(t)2)+eλtddt(|w(t)|2+α2w(t)2)=λeλt(|w(t)|2+α2w(t)2)2νeλtw(t)2++2eλtB(u(t))B(u),w(t)+2eλtg(t,ut)g(u),w(t)

    for t>0.

    Thanks to (2.3), (2.4) and (4.3),

    |B(u(t))B(u),w(t)|=|b(w(t),v(t),w(t)|C1w(t)uw(t)C1f(H1(Ω))3νLgw(t)2 (4.7)

    Hence, using a Young inequality we conclude that

    ddt(eλt(|w(t)|2+αw(t)2))eλt(λλ11+λα22ν+2C1f(H1(Ω))3νLg+Cg)w(t)2+1Cgeλtg(t,ut)g(u)2(H1(Ω))3.

    Therefore, integrating from 0 to t, we have

    eλt|w(t)|2|w(0)|2+α2w(0)2+1Cgt0eλsg(s,us)g(u)2(H1(Ω))3ds+(λλ11+λα22ν+2C1f(H1(Ω))3νLg+Cg)t0eλsw(s)2ds, (4.8)

    and taking into account hypothesis (H4), we obtain that

    eλt|w(t)|2|w(0)|2+α2w(0)2+Cg0heλsw(s)2ds+(λλ11+λα22ν+2C1f(H1(Ω))3νLg+2Cg)t0eλsw(s)2ds|u0u|2+α2u0u2+Cgϕu2L2V+(λλ11+λα22ν+2C1f(H1(Ω))3νLg+2Cg)t0eλsw(s)2ds. (4.9)

    If we have (4.5), then we can conclude that there exists λ>0 such that

    eλt|w(t)|2|u0u|2+α2u0u2+Cgϕu2L2V.

    Remark 4.3. It is worth noticing that in some applications, the constants Cg and Lg are closely related to each other (see for instance Example 3.5 in [10] or Example 1 in [5]), and it happens that CgLg. In this case, a sufficient condition implying (4.5) is

    C1f(H1(Ω))3<(νCg)2. (4.10)

    In the previous subsection we have obtained a result on the exponential convergence of solutions of our problem to the unique stationary solution, but we need the delay term satisfies some additional hypothesis, for example, when g contains a variable delay which is continuously differentiable. However, we will prove here that, using a different approach and weakening the assumptions it is possible obtain a result for these more general terms. This technique has been developed by Razumikhin (see Razumikhin [36][37]) in the framework of delay ordinary differential equations, and has recently been applied to some stochastic ordinary and partial differential equations (e.g., Caraballo et al. [8]). But it is worth mentioning that this approach requires some kind of continuity concerning the operators in the model and the delay term, and we also need to work with strong solutions.

    First, we prove the following result.

    Theorem 4.4. Assume g satisfies conditions (H1)–(H4) for any T>0, and for each ξCV the map t[0,+)g(t,ξ)(H1(Ω))3 is continuous. Suppose that for f(H1(Ω))3 there exists a stationary solution u for the problem (4.1), and such that, for some λ>0,

    νA(ϕ(0)u),ϕ(0)uB(ϕ(0))B(u),ϕ(0)u+g(t,ϕ)g(t,u),ϕ(0)u<λ(|ϕ(0)u|2+α2ϕ(0)u2),  t0, (4.11)

    provided that ϕCV satisfying ϕ(0)u, and

    ϕu2CVeλh(|ϕ(0)u|2+α2ϕ(0)u2). (4.12)

    Then, u is the unique stationary solution of (4.1) and for all ψCV, the solution of (1.2) corresponding to the initial data u=ψ in [h,0], which is denoted by u(t;ψ), satisfies

    |u(t;ψ)u|2+α2u(t;ψ)u2eλtψu2CV, t0. (4.13)

    Proof. Arguing by contradiction, assume that there is a ψCV such that (4.13) does not hold. Then, denoting

    σ=inf{t>0;|u(t;ψ)u|2+α2u(t;ψ)u2>eλtψu2CV},

    we obtain

    eλt(|u(t;ψ)u|2+α2u(t;ψ)u2)eλσ(|u(σ;ψ)u|2+α2u(σ;ψ)u2)=||ψu||2CV, (4.14)

    for all 0tσ, and there exists a sequence {tk}k1R+ such that tkσ as k, and

    eλtk(|u(tk;ψ)u|2+α2u(tk;ψ)u2)>eλσ(|u(σ;ψ)u|2+α2u(σ;ψ)u2). (4.15)

    On the other hand, it follows from (4.14) that

    |u(σ+θ;ψ)u|2eλh(|u(σ;ψ)u|2+α2u(σ;ψ)u2),

    for all hθ0, which, taking into account (4.11), implies

    νA(u(σ;ψ)u),u(σ;ψ)uB(u(σ;ψ))B(u),u(σ;ψ)u+g(σ,uσ(;ψ))g(σ,u),u(σ;ψ)u<λ(|u(σ;ψ)u|2+α2u(σ;ψ)u2). (4.16)

    As u(;ψ)C([h,+);V), from the continuity of the operators in our problem, we ensure the existence of ϵ>0 such that for each ϵ(0,ϵ],

    νA(u(t;ψ)u),u(t;ψ)uB(u(t;ψ))B(u),u(t;ψ)u+g(t,ut(;ψ))g(t,u),u(t;ψ)uλ(|u(t;ψ)u|2+α2 |u(t;ψ)u2), (4.17)

    for all t[σ,σ+ϵ]. Thus, writing w(t)=u(t;ψ)u, we have

    12ddt(|w(t)|2+α2w(t)2)=νAw(t),w(t)B(u(t;ψ))B(u),w(t)+g(t,ut(;ψ))g(t,u),w(t)

    for all t[σ,σ+ϵ], and integrating now we obtain

    eλ(σ+ϵ)(|w(σ+ϵ;ψ)|2+α2w(σ+ϵ;ψ)2)eλσ(|u(σ;ψ)u|2+α2u(σ;ψ)u2)=σ+ϵσλeλt(|w(t;ψ)|2+α2w(t;ψ)2)dt+σ+ϵσeλt(2νAw(t),w(t)2B(u(t;ψ))B(u),w(t))dt+σ+ϵσeλtg(t,ut(;ψ))g(t,u),w(t)dt0.

    Obviously this contradicts (4.15), and the proof is complete.

    For the uniqueness of the stationary solution, if ˆu is another stationary solution to (4.1), then u(t)ˆu is a solution of (1.2) with u0=ˆu and ϕ=ˆu, and therefore, by applying (4.6) with t going to +, we have that |ˆuu|20.

    Remark 4.5. It would be very interesting to have a sufficient condition which could be checked more easily in applications than (4.11). We establish one in the next Corollary.

    Corollary 4.6. Assume g satisfies conditions (H1)–(H4) for any T>0, and suppose that for any ξCV the mapping t[0,+)g(t,ξ)(H1(Ω))3 is continuous. Suppose that f(H1(Ω))3 is such that there exists a stationary solution u for the problem (4.1). If νLg>0 and

    ν+Lg(λ11+α2)+C1f(H1(Ω))3νLg<0, (4.18)

    then the stationary solution u of (4.1) is unique and there exists λ>0 such that for each ψCV, the solution u(t;ψ) of (1.2) corresponding to this initial datum, satisfies (4.13), i.e.,

    |u(t;ψ)u|2+α2u(t;ψ)u2eλtψu2CV, t0.

    Proof. Let ϕCV be such that ϕ(0)u and

    ϕu2CVeλh(|ϕ(0)u|2+α2ϕ(0)u2) (4.19)

    where λ>0 is to be chosen later. Then,

    νA(ϕ(0)u),ϕ(0)uB(ϕ(0))B(u),ϕ(0)u+g(t,ϕ)g(t,u),ϕ(0)uνϕ(0)u2+|B(ϕ(0))B(u),ϕ(0)u|+LgϕuCVϕ(0)uνϕ(0)u2+Lgeλh(λ11+α2)ϕ(0)u2+|B(ϕ(0))B(u),ϕ(0)u|.

    Using now (4.7), we obtain

    νA(ϕ(0)u),ϕ(0)uB(ϕ(0))B(u),ϕ(0)u+g(t,ϕ)g(t,u),ϕ(0)u(ν+Lgeλh(λ11+α2)+C1f(H1(Ω))3νLg)ϕ(0)u2. (4.20)

    If we denote

    μ=νLgeλh(λ11+α2)C1f(H1(Ω))3νLg,

    is easy to deduce that

    μϕ(0)u2min{μλ112,μ2α2}(|ϕ(0)u|2+α2ϕ(0)u2)

    If (4.18) holds, then there exists λ>0 such that

    λmin{μλ112,μ2α2}<0,

    and for this fixed λ, we can obtain from (4.18)

    νA(ϕ(0)u),ϕ(0)uB(ϕ(0))B(u),ϕ(0)u+g(t,ϕ)g(t,u),ϕ(0)uλ(|ϕ(0)u|2+α2ϕ(0)u2).

    The proof is now complete.

    Our aim in this subsection is to prove a sufficient condition for the exponential stability of stationary solutions to the Navier-Stokes-Voigt model with delay, using a Gronwall-like lemma. In this case, we do not need to specify any particular form of the delay as in the previous cases, but in the particular case of variable delay it is not necessary to impose neither differentiability nor continuity but only measurability of the variable delay function. Let us first recall the key tool for our analysis, which is a Gronwall-like inequality proved by H. Chen in [12].

    Lemma 4.7. ([12, Lemma 3.2]) Let y():[h,+)[0,+) be a function. Assume that there exist positive numbers γ,α1 and α2 such that γ>α2, and the following inequality holds:

    y(t){α1eγt+α2t0eγ(ts)supθ[h,0]y(s+θ)ds, t0,α1eγt, t[h,0]. (4.21)

    Then,

    y(t)α1eμt, for th,

    where μ(0,γ) is given by the unique root of the equation

    α2γμeμh=1

    in this interval.

    We state our stability result in the next theorem.

    Theorem 4.8. Assume that g(,) satisfies conditions (H1)–(H3) and f(H1(Ω))3. Assume also that uV is the unique stationary solution to (4.1). Then, u is exponentially stable if

    ν>C1u+Lg. (4.22)

    Proof. Let λ be a positive constant such that

    λ2(λ11+α2)(2ν2C1u2Lg)<0.

    Then, taking into account condition (H3) and the fact that νAu+Bufg(t,u)=0, if u() is a weak solution to the model (1.2) for the initial datum ϕ, we obtain, for t0,

    ddt(eλt(|u(t)u|2+α2u(t)u2))=λeλt(|u(t)u|2+α2u(t)u2)+eλtddt(|u(t)u|2+α2u(t)u2)=λeλt(|u(t)u|2+α2u(t)u2)+2eλtddt(u(t)u),u(t)u=λeλt(|u(t)u|2+α2u(t)u2)+2eλtνA(u(t)u),u(t)u+2eλt(B(u(t))B(u)),u(t)u+2eλtg(t,ut)g(t,u),u(t)uλeλt(|u(t)u|2+α2u(t)u2)2eλtνu(t)u2+2eλt(B(u(t))B(u)),u(t)u+2eλtLgutu2CV.

    Thanks to (2.3) and (2.5),

    |B(u(t))B(u),w(t)|=b(u(t)u,u,u(t)u)|C1uu(t)u2 (4.23)

    and we arrive at

    ddt(eλt(|u(t)u|2+α2u(t)u2))λeλt(|u(t)u|2+α2u(t)u2)2eλtνu(t)u2+2C1eλtuu(t)u2+2eλtLgutu2CVeλt[λ2(λ11+α2)2ν+2C1u+2Lg]utu2CV+λ2eλt(|u(t)u|2+α2u(t)u2). (4.24)

    Integrating (4.24) over the interval [0,t] gives

    eλt(|u(t)u|2+α2u(t)u2)|u(0)u|2+α2u(0)u2+λ2t0eλs(|u(s)u|2+α2u(s)u2)ds,

    and consequently,

    |u(t)u|2+α2u(t)u2eλt(|u(0)u|2+α2u(0)u2)+λ2t0eλ(ts)supθ[h,0](|u(s+θ)u|2+α2u(s+θ)u2)ds.

    Now, we can apply Lemma 4.7 denoting γ=λ,α2=λ2 and

    α1=supθ[h,0](|u(θ)u|2+α2u(θ)u2),

    since it is straightforward to see that, for t[h,0],

    |u(t)u|2+α2u(t)u2eλtsupθ[h,0](|u(θ)u|2+α2u(θ)u2).

    Then, the exponential stability of u follows from Lemma 4.7, namely, there exists μ(0,λ) such that

    |u(t)u|2+α2u(t)u2α1eλt

    for all th.

    In this subsection, we will compare in the particular case of forcing term with variable delay, the main results obtained by the three different methods described previously. Notice that, by straightforward computations, the value of constants Lg and Cg are

    Lg=Mλ1,Cg=Mem1h/2λ11ρ.

    Indeed, to check (H3),

    ||g(t,ξ)g(t,μ)||(H1(Ω))3λ1/21|G(ξ(ρ(t)))G(μ(ρ(t)))|Mλ1/21|ξ(ρ(t))μ(ρ(t))|Mλ11ξ(ρ(t))μ(ρ(t))Mλ11ξμCV,

    and, to check (H4),

    tτems||g(s,us)g(s,vs)||2(H1(Ω))3dsλ11tτems|G(u(sρ(s)))G(v(sρ(s)))|2dsλ11M2tτems|u(sρ(s))v(sρ(s))|2dsλ21M2tτemsu(sρ(s))v(sρ(s))2dsM2em1hλ21(1ρ)tτhemθu(θ)v(θ)2dθ,

    whenever ρC1([0,+)), ρ0 for all t0, h=supt0ρ(t) and ρ=supt0ρ(t)<1.

    Then, the sufficient condition provided by Theorem 4.2 reads ν>Mem1h/2λ11ρ and

    C1f(H1(Ω))3<(νMem1h/2λ11ρ)(νMλ1), (4.25)

    and we need to impose that the delay function is continuously differentiable.

    Next, Corollary 4.6 ensures exponential stability by simply assuming that ρ is a continuous function and the following condition holds:

    C1f(H1(Ω))3<(νMλ1(λ11+α2))(νMλ1) (4.26)

    Finally the condition in Theorem 4.8 is

    C1f(H1(Ω))3<(νMλ1)2. (4.27)

    Observe that em1h/21ρ>1, therefore, Mem1h/2λ11ρ>Mλ1, and then (4.23) implies (4.25). As for condition (4.24), observe that this depends on the value of λ11+α2, and this is related to the size of the domain Ω, since the first eigenvalue λ1 depends on this. Therefore, this condition can provide better or worse stability regions depending on the shape of the domain, and on the value of α.

    We have proved some results on the existence, uniqueness and asymptotic behaviour of the solutions for a three-dimensional Navier-Stokes-Voigt model with delay forcing term. Our assumptions are general enough to include several types of delay in the formulation (constant delay, variable delay with only measurable delay function, distributed delay, etc.). In particular, we have analyzed the exponential stability of the stationary solutions.

    We have studied the local stability of stationary solutions by several different methods: the classical Lyapunov function method, the Razumikhin-Lyapunov technique and another one based in a Gronwall-like lemma. On the other hand, the study of global long-time behavior of solutions to Navier-Stokes-Voigt equations, in 2D and 3D, has been recently considered in some particular cases of special delays (see, for instance, [15,17,38]). Therefore, it will be also interesting to carry out a similar global analysis of this model by proving the existence of attractors as well as the study of their geometrical structure in the abstract functional formulation that we have considered in this paper, and it is the reason we have first studied their stationary solutions and their stability. We plan to investigate these issues in a subsequent paper.

    Partially supported by the Spanish Ministerio de Ciencia, Innovación y Universidades (MCIU), Agencia Estatal de Investigación (AEI) and Fondo Europeo de Desarrollo Regional (FEDER) under the project PGC2018-096540-B-I00, and by Junta de Andalucía (Consejería de Economía y Conocimiento) under project US-1254251.

    The authors declare that they have no competing interest.



    [1] Z. Hou, L. Cheng, M. Tan, Decentralized robust adaptive control for the multiagent system consensus problem using neural networks, IEEE T. Syst. Man Cy. Part B, 39 (2009), 636–647. doi: 10.1109/TSMCB.2008.2007810
    [2] W. Zhu, D. Chen, Leader-following consensus of second-order multi-agents with multiple time-varying delays, Automatica, 46 (2010), 1994–1999. doi: 10.1016/j.automatica.2010.08.003
    [3] Y. Hong, G. Chen, Distributed observers design for leader-following control of multi-agent networks, Automatica, 44 (2008), 846–850. doi: 10.1016/j.automatica.2007.07.004
    [4] W. Chen, X. Li, L. Jiao, Quantized consensus of second-order continuous-time multi-agent systems with a directed topology via sampled data, Automatica, 49 (2013), 2236–2242. doi: 10.1016/j.automatica.2013.04.002
    [5] J. Fu, J. Wang, Adaptive consensus tracking of high-order nonlinear multi-agent systems with directed communication graphs, Int. J. Control, Autom Syst., 12 (2014), 919–929. doi: 10.1007/s12555-013-0325-0
    [6] C. Hua, Y. Li, X. Guan, Leader-following consensus for high-order nonlinear stochastic multiagent systems, IEEE T. Cybernetics, 47 (2017), 1882–1891.
    [7] W. Wang, C. Wen, J. Huang, Distributed adaptive asymptotically consensus tracking control of nonlinear multi-agent systems with unknown parameters and uncertain disturbances, Automatica, 47 (2017), 133–142.
    [8] W. Wang, C. Wen, J. Huang, J. Zhou, Adaptive consensus of uncertain nonlinear systems with event triggered communication and intermittent actuator faults, Automatica, 111 (2020), 108667. doi: 10.1016/j.automatica.2019.108667
    [9] K. Tee, S. Ge, E. Tay, Barrier Lyapunov functions for the control of output constrained nonlinear systems, Automatica, 45 (2009), 918–927. doi: 10.1016/j.automatica.2008.11.017
    [10] Y. Liu, J. Li, S. Tong, C. L. P. Chen, Neural network control-based adaptive learning design for nonlinear systems with full-state constraints, IEEE T. Neur. Net. Lear. Syst., 27 (2016), 1562–1571. doi: 10.1109/TNNLS.2015.2508926
    [11] Y. Liu, S. Lu, S. Tong, X. Chen, C. L. P. Chen, D. Li, Adaptive control-based barrier Lyapunov functions for a class of stochastic nonlinear systems with full state constraints, Automatica, 87 (2018), 83–93. doi: 10.1016/j.automatica.2017.07.028
    [12] K. Sun, S. Mou, J. Qiu, T. Wang, H. Gao, Adaptive fuzzy control for nontriangular structural stochastic switched nonlinear systems with full state constraints, IEEE T. Fuzzy Syst., 27 (2019), 1587–1601. doi: 10.1109/TFUZZ.2018.2883374
    [13] Y. Li, Y. Liu, S. Tong, Observer-based neuro-adaptive optimized control of strict-feedback nonlinear systems with state constraints, IEEE T. Neur. Net. Lear. Syst., 2021. DOI: 10.1109/TNNLS.2021.3051030.
    [14] J. Xia, J. Zhang, W. Sun, B. Zhang, Z. Wang, Finite-time adaptive fuzzy control for nonlinear systems with full state constraints, IEEE T. Syst. Man Cy. Syst., 49 (2019), 1541–1548. doi: 10.1109/TSMC.2018.2854770
    [15] H. Min, S. Xu, Z. Zhang, Adaptive finite-time stabilization of stochastic nonlinear systems subject to full-state constraints and input saturation, IEEE T. Automat. Contr., 66 (2021), 1306–1313. doi: 10.1109/TAC.2020.2990173
    [16] L. Shang, M. Cai, Adaptive practical fast finite-time consensus protocols for high-order nonlinear multi-agent systems with full state constraints, IEEE Access, 9 (2021), 81554–81563. doi: 10.1109/ACCESS.2021.3085843
    [17] D. Yao, C. Dou, N. Zhang, T. Zhang, Practical fixed-time adaptive consensus control for a class of multi-agent systems with full state constraints and input delay, Neurocomputing, 446 (2021), 156–164. doi: 10.1016/j.neucom.2021.03.032
    [18] K. Li, Y. Li, Fuzzy adaptive optimal consensus fault-tolerant control for stochastic nonlinear multi-agent systems, IEEE T. Fuzzy Syst., 2021. DOI: 10.1109/TFUZZ.2021.3094716.
    [19] F. Qu, S. Tong, Y. Li, Observer-based adaptive fuzzy output constrained control for uncertain nonlinear multi-agent systems, Inform. Sciences, 467 (2018), 446–463. doi: 10.1016/j.ins.2018.08.025
    [20] L. Wang, J. Dong, C. Xi, Event-triggered adaptive consensus for fuzzy output-constrained multi-agent systems with observers, J. Franklin I., 357 (2020), 82–105. doi: 10.1016/j.jfranklin.2019.09.033
    [21] Y. Liu, H. Zhang, J. Sun, Y. Wang, Adaptive fuzzy containment control for multi-agent systems with state constraints using unified transformation functions, IEEE T. Fuzzy Syst., 2020. DOI: 10.1109/TFUZZ.2020.3033376.
    [22] Y. Zhang, H. Liang, H. Ma, Q. Zhou, Z. Yu, Distributed adaptive consensus tracking control for nonlinear multi-agent systems with state constraints, Appl. Math. Comput., 326 (2018), 16–32.
    [23] D. Shen, J. Xu, Distributed learning consensus for heterogenous high-order nonlinear multi-agent systems with output constraints, Automatica, 97 (2018), 64–72. doi: 10.1016/j.automatica.2018.07.030
    [24] H. Ji, H. Xi, Adaptive output-feedback tracking of stochastic nonlinear systems, IEEE T. Automat. Contr., 51 (2006), 355–360. doi: 10.1109/TAC.2005.863501
    [25] D. Yang, X. Li, J. Shen, Z. Zhou, State-dependent switching control of delayed switched systems with stable and unstable modes, Math. Method. Appl. Sci., 41 (2018), 6968–6983. doi: 10.1002/mma.5209
    [26] D. Yang, X. Li, J. Qiu, Output tracking control of delayed switched systems via state-dependent switching and dynamic output feedback, Nonlinear Anal.-Hybrid Syst., 32 (2019), 294–305. doi: 10.1016/j.nahs.2019.01.006
    [27] J. Hu, G. Sui, X. Lv, X. Li, Fixed-time control of delayed neural networks with impulsive perturbations, Nonlinear Anal.-Model., 23 (2018), 904–920. doi: 10.15388/NA.2018.6.6
    [28] S. Shi, H. Min, S. Ding, Observer-based adaptive scheme for fixed-time frequency estimation of biased sinusoidal signals, Automatica, 127 (2021) 109559.
  • This article has been cited by:

    1. Yuming Qin, Huite Jiang, A generalized existence theorem of pullback attractors and its application to the 3D non-autonomous Navier-Stokes-Voigt equations, 2025, 0, 1937-1632, 0, 10.3934/dcdss.2025039
  • Reader Comments
  • © 2021 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(2628) PDF downloads(138) Cited by(4)

Figures and Tables

Figures(7)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog