1 Introduction

We are interested in the following problem

$$\begin{aligned} \frac{\textrm{d}}{\textrm{d}t}[k*(u-u_0)](t) + Au(t)&= f(t,u_t), \; t>0, \end{aligned}$$
(1.1)
$$\begin{aligned} u_0&= \varphi \in {\mathcal {B}}, \end{aligned}$$
(1.2)

where the unknown function u takes values in a separable Hilbert space H, the kernel \(k\in L^1_{loc}({\mathbb {R}}^+)\), the notation ‘\(*\)’ denotes the Laplace convolution, A is an unbounded linear self-adjoint operator, and \(f:{\mathbb {R}}^+\times {\mathcal {B}}\rightarrow H\) is a given nonlinear function. The admissible phase space \({\mathcal {B}}\) satisfies certain conditions that will be defined later. In our model, \(u_t\) represents the history of the state function u up to the time t, i.e. \(u_t(s) = u(t+s), s\le 0\).

It is worth pointing out that the system under consideration includes some important classical cases with respect to the kernel function k being of special ones (see, e.g. [14, 16]). Namely, if \(k(t)=g_{1-\mu }(t):={t^{-\mu }}/{\Gamma (1-\mu )}\), for \(\mu \in (0,1)\), then equation (1.1) is the fractional differential equations since the convolution represents \(D^\mu _0\), the Caputo fractional derivative of order \(\mu \). Regarding the fractional differential systems involving finite delays in Banach spaces, some results on (weak) stability and decay solutions were established in [1, 12, 13]. Based on the special features (e.g., the analyticity, subordinate principle) associated with the kernel \(g_{1-\mu }(t)\), the fractional differential equations can be considered in a more general framework:

$$\begin{aligned} \left\{ \begin{aligned} D^\mu _0 [x(t)-h(t,x_t)]&=Bx(t)+f(t,x(t),x_t),\; t>0\\ x(\theta )&=\varphi (\theta ), \theta \le 0, \end{aligned} \right. \end{aligned}$$
(1.3)

where B is the infinitesimal generator of an analytic semigroup on a Banach space X. Considering abstract neutral functional differential equations like (1.3) involving infinite delays, we refer the reader to [18, 21] for the existence of integral solutions, and [2] for existence of integral solutions with a certain decay rate. Noting that the approach in the mentioned works heavily relies on the point-wise decaying of the Mittag-Leffler functions \(E_{\mu ,\nu }(z)\), which is no longer available for the general nonlocal derivatives. Nevertheless, system (1.1) without delay has received considerable attention over decades. It appears in mathematical models of various processes in materials with memory (see, e.g. [5, 7, 23]). Particularly, Vergara and Zacher [29] mentioned that equation (1.1) with an appropriate class of kernels can be used to depict the anomalous diffusion phenomena which includes slow/ultraslow diffusions when \(H=L^2(\Omega ), \Omega \subset \mathbb R^N\), and \(A=-\Delta \) is the Laplacian associated with the homogeneous Dirichlet/Neumann boundary condition. We also refer to [14, 17] and the references therein for recent development on this trend.

It should be mentioned that, in modeling of physical/biological processes, the formulated system is usually subject to the history information, that is, a delay term comes into the model. A class of Caputo fractional integro-differential equations with bounded delays has been investigated recently in [4, 19] by Lyapunov-Razumikhin method. The authors in the recent work [16] studied (1.1) in the case of finite delay, i.e. \(\varphi \in C([-h,0];H)\), where some stability results were obtained. As far as we know, this is the first attempt dealing with stability analysis for nonlocal differential equations involving delays. In this work, we consider the case that \(\varphi \) belongs to the fading memory spaces, which were axiomatically introduced by Hale and Kato in [8]. This situation is entirely different from that in [16] due to the complicated structure of phase spaces. Our aim is to find a class of admissible phase spaces and conditions on the nonlinearity function f under which our problem is solvable, and its solution is stable/weakly stable. To this end, we first set the following fundamental hypotheses.

(A0):

The operator \(A:D(A)\subset H\rightarrow H\) is self-adjoint on H and its spectral \(\sigma (A)\) is bounded from below, that is, there exists \(\lambda _1:=\lambda _1(A)\in {\mathbb {R}}\) such that \(\sigma (A)\subset [\lambda _1,+\infty )\).

(K):

The kernel \(k\in L^1_{loc}(\mathbb R^+)\) is nonnegative and nonincreasing, and there exists a function \(l\in L^1_{loc}({\mathbb {R}}^+)\) such that \(k*l=1\) on \((0,\infty )\).

Hypothesis (K) enables us to get a representation of solutions for (1.1)–(1.2). This hypothesis has been used in a wide range of works (see [14, 16, 17, 22, 24, 29, 30]).

Let us give a brief on our approach. The well-posedness of linear equation is followed by Prüss’ theory of resolvent families and Lemma 2.2 2 below, which extends the recent result [14, Lemma 2.3]. Namely, the existence and qualitative properties of the solution operators are established for a general semibounded self-adjoint operator. The assumption (A0) also covers the case A has a negative spectrum, see Lemma 2.21. The solvability of (1.1)–(1.2) is obtained by a fixed point argument. This will be done by proving the compactness of the Cauchy operator in Proposition 2.3 without regularity assumption on the kernel, see Remark 2.1. The stability of the solution to (1.1)–(1.2) is proved by applying a new Halanay type inequality, which is more flexible, in comparison with the one in [16]. In addition, we utilize of the approach developed in [3, 16] to get the weakly asymptotic stability result, which relies on the fixed point principle for condensing maps on a special constructed subset. We find that the sufficient conditions for weak stability result, Theorem 4.4, only depend on the asymptotic behavior of the coefficients of the system for a large time. This phenomenon provides a compatible observation of existence result in finite time, where one has no restriction on the magnitude of Lipschitz constant of the nonlinear function. Our setting is more practical and relaxes some conditions proposed by previous works in the literature.

The paper is organized as follows. In Sect. 2, we collect some necessary results on the theory of resolvent, establish a compactness of the Cauchy operator and propose a new Halanay-type inequality. Section 3 is devoted to studying the existence of mild solutions and the dissipativity via the existence of absorbing sets. In Sect. 4, the stability results and the weakly asymptotic stability of the zero solution are formulated under certain assumptions on the nonlinearity as well as on the phase space. The last section presents an application to a class of nonlocal partial differential equations with infinite delays.

2 Preliminaries

2.1 Phase spaces

We recall in this subsection the axiomatic definition of the phase space \({\mathcal {B}}\), see [8]. The phase space \({\mathcal {B}}\) is a linear subspace consisting of functions from \((-\infty , 0]\) into H, which is furnished by a suitable seminorm \(\vert \cdot \vert _{{\mathcal {B}}}\) and satisfying the following. If a function \(v: (-\infty , T+\sigma ]\rightarrow H\) is such that \(v\vert _{[\sigma , T+\sigma ]}\in C([\sigma , T+\sigma ]; H)\) and \(v_{\sigma }\in {\mathcal {B}}\), then

  1. (B1)

    \(v_{t}\in {\mathcal {B}}\) for \(t\in [\sigma , T+\sigma ]\);

  2. (B2)

    the function \(t\mapsto v_{t}\) is continuous on \([\sigma , T+\sigma ]\);

  3. (B3)

    \(\vert v_{t}\vert _{{\mathcal {B}}}\le K(t-\sigma )\sup \nolimits _{\sigma \le s\le t}\Vert v(s)\Vert +M(t-\sigma )\vert v_{\sigma }\vert _{{\mathcal {B}}}\), where \(K, M: [0, \infty )\rightarrow [0, \infty )\) are independent of v, and K is continuous, M is locally bounded.

In the present work, we put a further assumption on \({\mathcal {B}}\):

  1. (B4)

    there exists \(\varrho >0\) such that \(\Vert \varphi (0)\Vert \le \varrho |\varphi |_{{\mathcal {B}}}\), for all \(\varphi \in {\mathcal {B}}\).

We recall here some examples of phase spaces \({\mathcal {B}}\). We refer the readers to the book by Hino, Mukarami and Naito [10] for more details. The first one is given by

$$\begin{aligned} C_{\gamma }=\{\varphi \in C((-\infty , 0]; H): \lim \limits _{\theta \rightarrow -\infty }e^{\gamma \theta } \varphi (\theta ) \text{ exists } \text{ in } H\}, \end{aligned}$$

for a given \(\gamma >0\). It easily sees that \(C_\gamma \) satisfies (B1)–(B3) with

$$\begin{aligned} K(t)=1,\,\, M(t)=e^{-\gamma t}, \end{aligned}$$

and \(C_\gamma \) is a Banach space with the following norm

$$\begin{aligned} \vert \varphi \vert _{{\mathcal {B}}}=\sup \limits _{\theta \le 0}e^{\gamma \theta }\Vert \varphi (\theta )\Vert . \end{aligned}$$

The second example is defined as follows. Assume that \(1\le p<+\infty , 0\le r<+\infty \) and a function \(g: (-\infty , -r]\rightarrow {\mathbb {R}}\) is nonnegative, Borel measurable on \((-\infty , -r)\). Let \(CL_g^{p}\) denote a class of functions \(\varphi : (-\infty , 0] \rightarrow H\) such that \(\varphi \) is continuous on \([-r, 0]\) and \(g(\theta )\Vert \varphi (\theta )\Vert ^{p}\in L^{1}(-\infty , -r)\). The associated seminorm in \(CL_g^{p}\) is given by

$$\begin{aligned} \vert \varphi \vert _{CL^p_g}=\sup \limits _{-r\le \theta \le 0}\Vert \varphi (\theta )\Vert +\Bigr [\int _{-\infty }^{-r}g(\theta )\Vert \varphi (\theta )\Vert ^{p}\, \textrm{d}\theta \Bigr ]^{\frac{1}{p}}. \end{aligned}$$

Furthermore, suppose that

$$\begin{aligned}&\int _{s}^{-r}g(\theta )\textrm{d}\theta <+\infty , \text{ for } \text{ every } s\in (-\infty , -r) \text{ and } \end{aligned}$$
(2.1)
$$\begin{aligned}&g(s+\theta )\le G(s)g(\theta ) \text{ for } s\le 0 \text{ and } \theta \in (-\infty , -r), \end{aligned}$$
(2.2)

where \(G: (-\infty , 0]\rightarrow {\mathbb {R}}^{+}\) is a locally bounded function. It is shown in [10], \(CL_g^{p}\) satisfies (B1)–(B3) provided that (2.1)–(2.2) hold true. More precisely,

$$\begin{aligned}&K(t)={\left\{ \begin{array}{ll} 1&{}\quad \text{ for } 0\le t\le r,\\ 1+\Bigr [\int _{-t}^{-r}g(\theta )\, \textrm{d}\theta \Bigr ]^{\frac{1}{p}}&{}\quad \text{ for } t>r; \end{array}\right. } \end{aligned}$$
(2.3)
$$\begin{aligned}&M(t)={\left\{ \begin{array}{ll} \max \Bigr \{1+\Bigr [\int _{-t}^{-r}g(\theta )\, \textrm{d}\theta \Bigr ]^{\frac{1}{p}}, G(-t)^{\frac{1}{p}}\Bigr \}&{}\quad \text{ for } 0\le t\le r,\\ \max \Bigr \{\Bigr [\int _{-t}^{-r}g(\theta )\, \textrm{d}\theta \Bigr ]^{\frac{1}{p}}, G(-t)^{\frac{1}{p}}\Bigr \}&{}\quad \text{ for } t>r. \end{array}\right. } \end{aligned}$$
(2.4)

2.2 The resolvent families

Consider the following scalar Volterra equations which describe the relaxation functions

$$\begin{aligned}&s(t) + \lambda (l*s)(t) =1, \quad t\ge 0, \end{aligned}$$
(2.5)
$$\begin{aligned}&r(t) + \lambda (l*r)(t) = l(t), \quad t>0. \end{aligned}$$
(2.6)

The solvability of s and r was mentioned in [20]. The solutions of (2.5) and (2.6) are denoted by \(s(\cdot ,\lambda )\) and \(r(\cdot ,\lambda )\), respectively. The kernel l is said to be completely positive if and only if for every \(\lambda >0\), \(s(\cdot )\) and \(r(\cdot )\) take nonnegative values. An equivalent criterion is that (see [5, Theorem 2.2]), there exist \(\alpha \ge 0\) and a nonnegative and nonincreasing kernel \(k\in L^1_{loc}({\mathbb {R}}^+)\) which satisfy \(\alpha l(t)+ l*k(t)=1\) for all \(t>0\). Hence, our assumption (K) yields that l is completely positive and particularly, l takes nonnegative values by [5, Proposition 2.1 (1)]. Consequently, the functions \(s(\cdot ,\lambda )\) and \(r(\cdot ,\lambda )\) take nonnegative values (for even \(\lambda \le 0\), see also explanation in [30]). We remind some further properties of these relaxation functions.

Proposition 2.1

[14, 30] Let the hypothesis (K) hold. Then for every \(\lambda \in {\mathbb {R}}\), \(s(\cdot ,\lambda ),r(\cdot ,\lambda )\in L^1_{loc}({\mathbb {R}}^+)\). In addition, we have:

  1. (1)

    The function \(s(\cdot ,\lambda )\) is nonnegative and nonincreasing. Moreover, for \(\lambda >0,\)

    $$\begin{aligned} s(t,\lambda )\left[ 1+\lambda \int _0^t l(\tau )\textrm{d}\tau \right] \le 1, \quad \forall t\ge 0. \end{aligned}$$
    (2.7)

    Hence if \(l\not \in L^1({\mathbb {R}}^+)\) then \(\lim \nolimits _{t\rightarrow \infty }s(t,\lambda )=0\) for every \(\lambda >0\).

  2. (2)

    The function \(r(\cdot , \lambda )\) is nonnegative and one has

    $$\begin{aligned}&s(t,\lambda ) =1-\lambda \int _0^t r(\tau ,\lambda )\textrm{d}\tau = k*r(\cdot ,\lambda )(t), \quad t\ge 0, \end{aligned}$$

    so \(\int _0^t r(\tau ,\lambda )\textrm{d}\tau \le \lambda ^{-1}, \;\forall t>0\). If \(l\not \in L^1({\mathbb {R}}^+)\) then \(\int _0^\infty r(\tau ,\lambda )\textrm{d}\tau = \lambda ^{-1}\) for every \(\lambda >0\).

  3. (3)

    For each \(t>0\), the functions \(\lambda \mapsto s(t,\lambda )\) and \(\lambda \mapsto r(t,\lambda )\) are nonincreasing in \({\mathbb {R}}\).

  4. (4)

    Equation (2.5) is equivalent to the problem

    $$\begin{aligned} \frac{\textrm{d}}{\textrm{d}t}[k*(s-1)] + \lambda s&= 0,\; s(0) =1. \end{aligned}$$
  5. (5)

    Let \(v(t) = s(t,\lambda )v_0 + (r(\cdot ,\lambda )*g)(t)\), here \(g\in L^1_{loc}({\mathbb {R}}^+)\). Then v solves the problem

    $$\begin{aligned} \frac{\textrm{d}}{\textrm{d}t}[k*(v-v_0)](t) + \lambda v(t)&= g(t),\; v(0) = v_0. \end{aligned}$$

Using spectral theorem for self-adjoint operator [26, Theorem 1.7], the hypothesis (A0) implies that there exist a measure space \((\Xi ,\textrm{d}\mu )\), a unitary map \(U:L^2(\Xi ,\textrm{d}\mu )\rightarrow H\) and a real-valued function a on \(\Xi \) such that

$$\begin{aligned} U^{-1}AU f(\xi )=a(\xi )f(\xi ),\; Uf\in D(A). \end{aligned}$$
(2.8)

Note that for \(f\in L^2(\Xi ,\textrm{d}\mu )\), \(Uf\in D(A)\) iff \(M_af(\cdot )=a(\cdot )f(\cdot )\) belongs to \(L^2(\Xi ,\textrm{d}\mu )\).

Based on this spectral representation of A, the Borelian functional calculus of A is given by

$$\begin{aligned} \left( U^{-1}g(A)Uv\right) (\xi )=g(a(\xi ))v(\xi ), \text { for almost every }\xi \in \Xi , \end{aligned}$$
(2.9)

for arbitrary Borel function \(g:{\mathbb {R}}\rightarrow {\mathbb {C}}\). In general, g(A) is unbounded linear self-adjoint in H for an arbitrary Borel real-valued function g. If g is bounded in \({\mathbb {R}}\) then so is g(A) and \(\Vert g(A)\Vert _{L(H)}\le \Vert g\Vert _{L^\infty ({\mathbb {R}})}\).

The spectral boundedness from below of A implies that

$$\begin{aligned} a(\xi ) \in [\lambda _1,+\infty ), \text { for almost every }\xi \in \Xi . \end{aligned}$$

Therefore, the functional g(A) only depends on the essential value of g in \([\lambda _1,+\infty )\). In particular, if \(g\in L^\infty ([\lambda _1,\infty ),\textrm{d}\mu )\) then g(A) is a bounded linear map in H and furthermore

$$\begin{aligned} \Vert g(A)\Vert _{L(H)}\le \mathop {\mathrm{ess\,sup}}\nolimits _{\xi \in \Xi }|g(a(\xi ))|. \end{aligned}$$
(2.10)

Note that if \(\lambda _1\ge 0\) then for \(\gamma \ge 0\), the fractional power of A can be defined as follows

$$\begin{aligned} D(A^\gamma )&= \left\{ Uw\in H: w\in L^2(\Xi ,\textrm{d}\mu ), \left( a(\xi )\right) ^\gamma w(\xi )\in L^2(\Xi ,\textrm{d}\mu ) \right\} ,\\ U^{-1}A^\gamma Uw(\xi )&= a(\xi )^{\gamma } w(\xi ), Uw\in D(A^\gamma ). \end{aligned}$$

Let \(V_\gamma = D(A^\gamma )\). Then \(V_\gamma \) is a Banach space endowed with the norm

$$\begin{aligned} \Vert v\Vert _{D(A^\gamma )}= \left( \int _{\Xi }\left( 1+|a(\xi )|^{2\gamma }\right) |U^{-1}v(\xi )|^2\textrm{d}\mu \right) ^{\frac{1}{2}}. \end{aligned}$$

For \(\lambda _1>0\), this is equivalent to the following norm

$$\begin{aligned} \Vert v\Vert _{\gamma }=\Vert A^\gamma v\Vert _H = \left( \int _{\Xi }|a(\xi )|^{2\gamma }|U^{-1}v(\xi )|^2\textrm{d}\mu \right) ^{\frac{1}{2}}. \end{aligned}$$
(2.11)

Moreover, for \(\gamma >0\), \(V_{-\gamma }\) can be identified with the dual space \(V_\gamma ^*\) of \(V_\gamma \).

By formula (2.9) and properties of the functions \(s(t,\mu ), r(t,\mu )\), we now define the resolvent operators

$$\begin{aligned} U^{-1}S(t,A)Uv(\xi )&= s(t,a(\xi ))v(\xi ),\xi \in \Xi ,t\ge 0, Uv\in H, \end{aligned}$$
(2.12)
$$\begin{aligned} U^{-1}R(t,A)Uv(\xi )&= r(t,a(\xi ))v(\xi ), \xi \in \Xi , t>0, Uv\in H. \end{aligned}$$
(2.13)

Obviously, \(S(t):=S(t,A)\) and \(R(t):=R(t,A)\) are linear self-adjoint operators in H and fulfill the following fundamental relation

$$\begin{aligned} S'(t,A)=-AR(t,A), t>0, \end{aligned}$$
(2.14)

due to Proposition 2.1(2) and the relation (2.12)–(2.13). In the following lemma, we prove some properties of S(t), R(t) which extend the recent result [14, Lemma 3.2]. By relation (2.14), the statement in Lemma 2.2 (2) below implies that S(tA) is differentiable in the sense of Prüss [23, Definition 1.4]. A consequence of (2.17) is a smoothing effect of the solution operator. This estimate plays an important role in analyzing semilinear nonlocal evolution equations since the assumption on the nonlinearity can be relaxed considerably, as mentioned in [23, Section 13.5].

Lemma 2.2

Let \(\{S(t,A)\}_{t\ge 0}\) and \(\{R(t,A)\}_{t > 0},\) be defined by (2.12) and (2.13), respectively and \(T>0\) be given.

  1. (1)

    For each \(v\in H\), \(S(\cdot ,A)v\in C([0,T];H)\) and \(AS(\cdot ,A)v\in C((0,T];H)\). Moreover,

    $$\begin{aligned}&\Vert S(t,A)v\Vert \le s(t,\lambda _1)\Vert v\Vert ,\; t\in [0,T]; \\&\Vert AS(t,A)v\Vert \le \left\{ \begin{aligned}&\frac{\Vert v\Vert }{(1*l)(t)},&\quad \text {if }\lambda _1\ge 0,\\&|\lambda _1|s(t,-|\lambda _1|)\Vert v\Vert ,&\quad \text {if }\lambda _1<0, \end{aligned} \; \right. \end{aligned}$$

    for \(t\in (0,T]\).

  2. (2)

    Let \(v\in H\). Then \(R(\cdot ,A)v\in C((0,T];H)\). Furthermore,

    $$\begin{aligned}&\Vert R(t,A)v\Vert \le r(t,\lambda _1)\Vert v\Vert , \; t\in (0,T], \end{aligned}$$
    (2.15)
    $$\begin{aligned}&\Vert AR(t,A)v\Vert \le r(t,\lambda _1)\Vert Av\Vert , v\in D(A), t>0. \end{aligned}$$
    (2.16)

    In particular, for \(t>0\) one has \(\Vert S'(t,A)v\Vert \le r(t,\lambda _1)\Vert v\Vert _{D(A)}\) for all \(v\in D(A)\).

  3. (3)

    Assume further that \(\lambda _1>0\). Then the convolution with R possesses a smoothing effect in the sense that if \(g\in C([0,T];V_\gamma ), \gamma \ge 0\) then \(A(R*g) \in C([0,T];V_{\gamma -\frac{1}{2}})\)

    $$\begin{aligned} \Vert A(R*g)(t)\Vert _{V_{\gamma -\frac{1}{2}}}\le \left( \int _0^t r(t-\tau ,\lambda _1) \Vert g(\tau )\Vert _{V_\gamma }^2 \textrm{d}\tau \right) ^{\frac{1}{2}},\; t\in [0,T]. \end{aligned}$$
    (2.17)

Proof

The first part in (1) and (2) follow by the same argument as in [14, Lemma 2.3], so we verify only the remain statement in (1). By (2.10), one has

$$\begin{aligned} \Vert s(t,A)\Vert _{L(H)}\le \sup _{\lambda \ge \lambda _1}s(t,\lambda )=s(t,\lambda _1), \end{aligned}$$
(2.18)

where the last relation follows from the monotonicity of \(s(t,\cdot )\) with respect to \(\lambda \). Analogously, one also gets

$$\begin{aligned} \Vert AS(t,A)\Vert _{L(H)}&\le \sup _{\xi } |a(\xi )|s(t,a(\xi )) \end{aligned}$$
(2.19)
$$\begin{aligned}&= \sup _{\lambda \ge \lambda _1} |\lambda |s(t,\lambda )\le \sup _{\lambda \ge -|\lambda _1|} |\lambda |s(t,\lambda ) \end{aligned}$$
(2.20)
$$\begin{aligned}&=\max \left\{ \sup _{-|\lambda _1|\le \lambda \le 0}|\lambda |s(t,\lambda ),\sup _{\lambda >0}\lambda s(t,\lambda ) \right\} \end{aligned}$$
(2.21)
$$\begin{aligned}&\le \max \left\{ |\lambda _1|s(t,-|\lambda _1|), \frac{1}{1*l(t)}\right\} , \end{aligned}$$
(2.22)

here the last inequality follows from Proposition 2.1 (1).

The proof of the first part in (3) goes similarly the one above, hence we show only the last estimate (2.17). Using the representation

$$\begin{aligned} U^{-1}A(R*U{\hat{g}})(t,\xi )&=\int _0^t a(\xi )r(t-\tau ,a(\xi ))\hat{g}(\tau ,\xi )\textrm{d}\tau , \end{aligned}$$

where \({\hat{g}}(t,\cdot ) = U^{-1}g(t)\), we have

$$\begin{aligned} \Vert AR*g(t)\Vert _{V_{\gamma -1/2}}^2&= \int _{\Xi } a(\xi )^{2\gamma -1} \left( \int _0^t a(\xi )r(t-\tau , a(\xi )){\hat{g}}(\tau ,\xi ) \textrm{d}\tau \right) ^2\textrm{d}\mu , \end{aligned}$$

thanks to (2.11). Then utilizing the Hölder inequality, we get

$$\begin{aligned}&\Vert AR*g(t)\Vert _{V_{\gamma -1/2}}^2 \\&\quad \le \int _{\Xi } a(\xi )^{2\gamma -1}\left( \int _0^t a(\xi )r(t-\tau , a(\xi ))\textrm{d}\tau \right) \left( \int _0^t a(\xi )r(t-\tau , a(\xi )) |{\hat{g}}(\tau ,\xi )|^2\textrm{d}\tau \right) \textrm{d}\mu \\&\quad \le \int _{\Xi } (1-s(t,a(\xi ))\left( \int _0^t a(\xi )^{2\gamma } r(t-\tau , a(\xi )) |{\hat{g}}(\tau ,\xi )|^2\textrm{d}\tau \right) \textrm{d}\mu \\&\quad \le \int _0^t \left( \int _{\Xi }r(t-\tau , a(\xi )) a(\xi )^{2\gamma } |{\hat{g}}(\tau ,\xi )|^2\textrm{d}\mu \right) \textrm{d}\tau \\&\quad \le \int _0^t \left( r(t-\tau , \lambda _1) \int _{\Xi }a(\xi )^{2\gamma } |{\hat{g}}(\tau ,\xi )|^2\textrm{d}\mu \right) \textrm{d}\tau = \int _0^t r(t-\tau , \lambda _1) \Vert g(\tau )\Vert _{V_\gamma }^2 \textrm{d}\tau , \end{aligned}$$

which ensures (2.17). In particular, \(\Vert R*g\Vert _{C([0,T];V_{\gamma +1/2})}\le \frac{1}{\sqrt{\lambda _1}}\Vert g\Vert _{C([0,T],V_\gamma )}\). This is the half smoothing effect of the resolvent operator R. \(\square \)

Let E and F be Banach spaces. The notations \({\mathcal {L}}(E,F), {\mathcal {K}}(E,F)\) stand for spaces of bounded linear operators, linear compact operators from E to F, respectively. Note that \({\mathcal {K}}(E,F)\) is closed subset in \({\mathcal {L}}(E,F)\) with respect to the operator norm.

To gain the compactness of the solution operators, we need further assumption as follows:

(A):

The operator \(A:D(A)\subset H\rightarrow H\) is nonnegative, self-adjoint on H with compact resolvent.

This assumption guarantees that H possesses an orthonormal basis \(\{e_n\}_{n=1}^\infty \), where \(e_n, n\ge 1\) are eigenfunctions of the operator A with corresponding eigenvalues \(\lambda _n>0\). The domain

$$\begin{aligned} D(A) = \left\{ v = \sum _{n=1}^\infty v_ne_n: \sum _{n=1}^\infty \lambda _n^2v_n^2 <\infty \right\} , \end{aligned}$$

and A admits the presentation

$$\begin{aligned} Av = \sum _{n=1}^\infty \lambda _n v_n e_n,\; v_n = (v,e_n), v\in D(A). \end{aligned}$$

The assumption (A) implies that \(0<\lambda _1\le \lambda _2\le \cdots \le \lambda _n \rightarrow \infty \) as \(n\rightarrow \infty \). In this case, \(\Xi \) is the set \({\mathbb {N}}\) of natural numbers and the measure \(\textrm{d}\mu \) is thus the counting measure, the function \(a(n)=\lambda _n, \forall n\in {\mathbb {N}}\) and the unitary map \(U:L^2({\mathbb {N}},\textrm{d}\mu )\rightarrow H\) is given by

$$\begin{aligned} f=(f_1,f_2,\ldots ,f_n,\ldots )\in L^2({\mathbb {N}})\mapsto Uf=\sum _{k=1}^\infty f_k e_k\in H. \end{aligned}$$

For a real number s we denote \(X_s=C([0,T];D(A^s))\). We need the following result to investigate the existence results.

Proposition 2.3

Let assumptions (A) and (K) hold. Then the operator

$$\begin{aligned} Q:C([0,T];D(A^s))\rightarrow C([0,T];D(A^{s+1/2})), f\mapsto Qf(t):=R*f(t) \end{aligned}$$

is compact for any \(s\in {\mathbb {R}}\).

Proof

Based on the approximation argument, the proof is divided into several steps.

Step 1. We first remind that for a given \(g\in C[0,T]\), the convolution map \({\mathcal {C}}_g :C[0,T]\rightarrow C[0,T], v\mapsto g*v\) is compact. This is a classical result, but for the convenience of the readers, we provide a proof here. Fix any bounded subset \(D\subset C[0,T]\), that is, there exists a positive constant \(R>0\) such that

$$\begin{aligned} \Vert v\Vert \le R, \quad \forall v\in D. \end{aligned}$$

Clearly, \(|g*v(t)|\le \Vert g\Vert _{L^1(0,T)}\max \nolimits _{t\in [0,T]}|v(t)|, v\in D\), which implies the point-wise bounded of \({\mathcal {C}}_g(D)\).

On the other hand, for any \(\epsilon >0\), by the uniform continuity of g on [0, T], one chooses a positive number \(\delta <\epsilon /(2R\Vert g\Vert +1)\) such that

$$\begin{aligned} |g(s_1)-g(s_2)|\le \frac{\epsilon }{2RT} \text { for any }s_1,s_2\in [0,T], |s_1-s_2|\le \delta . \end{aligned}$$

For any \(t_1,t_2\in [0,T]\), \(0<t_2-t_1<\delta \) and \(v\in D\), one has

$$\begin{aligned} |g*v(t_2)-g*v(t_1))|&\le \int _0^{t_1}|g(t_1-\tau )-g(t_2-\tau )||v(\tau )|\textrm{d}s\\&\quad +\int _{t_1}^{t_2}|g(t_2-\tau )v(\tau )|\textrm{d}s\\&\le \frac{\epsilon }{2RT} \int _0^T |v(\tau )|\textrm{d}s+\max _{\tau \in [0,T]} |v(\tau )||t_1-t_2|\max _{\tau \in [0,T]}|g(\tau )|\\&\le \left( \frac{\epsilon }{2RT} T+\Vert g\Vert \delta \right) \sup _{v\in D}\Vert v\Vert \le \epsilon , \end{aligned}$$

for any \(v\in D\). Therefore, the equi-continuity of \(\mathcal C_g(D)\) is testified. Thus, \({\mathcal {C}}_g(D)\) is relatively compact in C[0, T] by Arzelà–Ascoli Theorem.

Step 2. Extend the statement above to the singular kernel. For a given \(g\in L^1(0,T)\) Then \(g*:C[0,T]\rightarrow C[0,T]\) is compact. Indeed, by density of smooth functions in \(L^1(0,T)\), one can choose a sequence of continuous function \(g_n\) such that \(g_n\) converges to g in \(L^1(0,T)\). Then, we have

$$\begin{aligned} \Vert ({{\mathcal {C}}_g}_n-{{\mathcal {C}}_g})v\Vert&=\sup _{t\in [0,T]}|\int _0^t (g_n(t-\tau )-g(t-\tau ))v(\tau )\textrm{d}\tau |\\&\le \sup _{t\in [0,T]}\int _0^t |g_n(t-\tau )-g(t-\tau )|.|v(\tau )|\textrm{d}\tau \\&\le \Vert g_n-g\Vert _{L^1(0,T)}\Vert v\Vert . \end{aligned}$$

Thus, \(\lim _{n\rightarrow \infty }\Vert {{\mathcal {C}}_g}_n-{\mathcal C_g}\Vert _{{\mathcal {L}}(C[0,T])}=0\), which implies the compactness of \({{\mathcal {C}}_g}\).

Step 3. Let denote

$$\begin{aligned} Q_n f(t)=\sum _{k=1}^n \left( \int _0^t r(t-\tau ,\lambda _k)f_k(\tau )\textrm{d}\tau \right) e_k \end{aligned}$$

for any \(f=\sum _{k=1}^\infty f_k(t)e_k\in C([0,T];D(A^s))\).

By Step 2, \(Q_n\) is a compact operator from \(C([0,T];D(A^s))\) to C([0, T]; \(D(A^{s+1/2}))\).

Step 4. By Step 3, it reduces to show that \(Q_n\) converges to Q with respect to the operator norm in \({\mathcal {L}}(X_s,X_{s+1/2})\). Indeed, we have

$$\begin{aligned}&\Vert (Q-Q_n)v(t)\Vert ^2_{D(A^{s+1/2})}\\&\quad =\sum _{k>n} |\lambda _k^{1+2s}\int _0^t r(t-\tau ,\lambda _k)v_k(\tau )\textrm{d}\tau |^2\\&\quad \le \sum _{k>n} \int _0^t \lambda _kr(t-\tau ,\lambda _k)\textrm{d}\tau \cdot \int _0^t r(t-\tau ,\lambda _k)|\lambda _k^s v_k(\tau )|^2\textrm{d}\tau \\&\quad \text { (by H}\ddot{\textrm{o}}\text {lder's inequality)}\\&\quad \le \int _0^t r(t-\tau ,\lambda _n) \sum _{k>n}|\lambda _k^s v_k(\tau )|^2\textrm{d}\tau \\&\qquad \quad \text {(since }\int _0^t \lambda _kr(\tau ,\lambda _k)\textrm{d}\tau =1-s(t,\lambda _k)\le 1\text { and }r(\cdot ,\lambda _k)\\&\quad \le r(\cdot ,\lambda _n)\text { for }k>n)\\&\quad \le \int _0^t r(t-\tau ,\lambda _n) \Vert v(\tau )\Vert ^2_{D(A^s)}\textrm{d}\tau \\&\quad \le \left( \int _0^t r(t-\tau ,\lambda _n)\textrm{d}\tau \right) \sup _{s\in [0,T]}\Vert v(\tau )\Vert ^2_{D(A^s)}\\&\quad =\frac{1-s(t,\lambda _n)}{\lambda _n} \Vert v\Vert ^2_{X_s}. \end{aligned}$$

Hence, we obtain

$$\begin{aligned}&\Vert Q_n-Q\Vert _{X_{s+1/2}}=\sup _{t\in [0,T]}\Vert (Q-Q_n)v(t)\Vert ^2_{D(A^{s+1/2})}\le \frac{1}{\lambda _n} \Vert v\Vert ^2_{X_s}. \end{aligned}$$

In other word, we get

$$\begin{aligned} \Vert Q-Q_n\Vert _{{\mathcal {L}}(X_s,X_{s+1/2})}\le \lambda _n^{-1/2}\rightarrow 0 \text { as }n\rightarrow \infty . \end{aligned}$$

This finishes the proof. \(\square \)

Remark 2.1

The standard argument for checking the compactness of a subset in \(C([0,T],D(A^{s+1/2}))\) is applying Arzelà–Ascoli Theorem directly. However, due to the singularity of the kernel l (so \(r(\cdot ,\lambda )\)), it is difficult to testify the equi-continuity of Q(D) directly without further regularity assumption on the function l. So the proof of compactness for Q in this work requires less conditions than those in [15, Lemma 3.5].

2.3 Halanay type inequality

We denote by \(BC({\mathbb {R}}^+; X)\) the space of continuous and bounded functions defined on \({\mathbb {R}}^+\) taking values in a Banach space X. It is a Banach space with the norm given by \(\Vert y\Vert _{BC}=\sup \nolimits _{t\ge 0}\Vert y(t)\Vert \). Let \(BC(\mathbb R^+)=BC({\mathbb {R}}^+; {\mathbb {R}})\) and \(BC_0:=\{ v\in BC(\mathbb R^+)\bigm |\lim \nolimits _{t\rightarrow \infty } v(t)=0\}\). We verify now a Halanay type inequality in the integral form, which plays a crucial role in our approach.

Proposition 2.4

(Halanay type inequality) Let v be a continuous and nonnegative function on \({\mathbb {R}}^+\). Assume that for any \(t>0\), it holds

$$\begin{aligned} v(t)&\le p(t) + \int _0^t r(t-\tau , a) q(\tau )\textrm{d}\tau +b \int _0^t r(t-\tau , a)\sup _{\xi \in [\tau -\rho (\tau ), \tau ]}v(\xi )\textrm{d}\tau , \end{aligned}$$
(2.23)

where \(p, q\in BC({\mathbb {R}}^+)\), \(a>b\ge 0\), and \(\rho \) is a given function such that \(t\ge \rho (t)\) for \(t\ge 0\). Then, \(v\in BC({\mathbb {R}}^+)\) and

$$\begin{aligned} v(t)\le \big (\Vert p\Vert _{BC}+\Vert r(\cdot , a)*q\Vert _{BC}\big )\frac{a}{a-b},\; \forall t\ge 0. \end{aligned}$$
(2.24)

Moreover, if \(\lim \nolimits _{t\rightarrow \infty }(t-\rho (t))=\infty \), then

$$\begin{aligned} \limsup \limits _{t\rightarrow \infty } v(t) \le \limsup \limits _{t\rightarrow \infty }\Big ( p(t)+\big (r(\cdot , a)*q\big ) (t)\Big )\dfrac{a}{a-b}. \end{aligned}$$
(2.25)

In particular, for any \(\epsilon >0\), there exists \(T(\epsilon )>0\) such that

$$\begin{aligned} v(t)\le \frac{ar^*}{a-b}+\epsilon ,\; \forall t\ge T(\epsilon ), \end{aligned}$$

here \(r^*= \limsup \limits _{t\rightarrow \infty } p(t)+\limsup \limits _{t\rightarrow \infty }r(\cdot , a)*q(t)\).

Proof

First, we prove (2.24). By (2.23), for all \(t\in [0,T]\), one has

$$\begin{aligned} v(t)&\le \Vert p +r(\cdot , a)*q\Vert _{BC}+b\sup _{\xi \in [0, T]}v(\xi ) \int _0^t r(t-\tau , a)\textrm{d}\tau \\&\le \Vert p\Vert _{BC} +\Vert r(\cdot , a)*q\Vert _{BC}+b\sup _{\xi \in [0, T]}v(\xi ) \frac{1-s(t, a)}{a}\\&\le \Vert p\Vert _{BC} +\Vert r(\cdot , a)*q\Vert _{BC}+\frac{b}{a}\sup _{\xi \in [0, T]}v(\xi ). \end{aligned}$$

It implies

$$\begin{aligned} \sup _{\xi \in [0, T]}v(\xi )\le \Big (\Vert p\Vert _{BC} +\Vert r(\cdot , a)*q\Vert _{BC}\Big ) \frac{a}{a-b}. \end{aligned}$$

Let \(T\rightarrow \infty \), we get

$$\begin{aligned} \sup _{\xi \in [0, \infty )}v(\xi )\le \Big (\Vert p\Vert _{BC} +\Vert r(\cdot , a)*q\Vert _{BC}\Big ) \frac{a}{a-b}. \end{aligned}$$

Thus, (2.24) is verified.

We next show that (2.25) holds. Since \(t-\rho (t)\rightarrow \infty \) as \(t\rightarrow \infty \), it follows that for any \(T>0\), there exists \(T_1=T_1(T)>0\) such that

$$\begin{aligned} t-\rho (t)\ge T, \quad \forall t\ge T_1, \end{aligned}$$

and \(T_1\rightarrow \infty \) as \(T\rightarrow \infty \). Using (2.23) with \(t\ge T_1\) yields

$$\begin{aligned} v(t)&\le p(t) + \big (r(\cdot , a)*q\big ) (t) +b \int _0^{T_1} r(t-\tau , a)\sup _{\xi \in [\tau -\rho (\tau ), \tau ]}v(\xi )\textrm{d}\tau \\&\quad +b \int _{T_1}^t r(t-\tau , a)\sup _{\xi \in [\tau -\rho (\tau ), \tau ]}v(\xi )\textrm{d}\tau \\&\le p(t) + \big (r(\cdot , a)*q\big ) (t) +b \Vert v\Vert _{BC} \int _0^{T_1} r(t-\tau , a)\textrm{d}\tau \\&\quad +b\sup _{\xi \ge T}v(\xi ) \int _{T_1}^t r(t-\tau , a)\textrm{d}\tau \\&\le p(t) + \big (r(\cdot , a)*q\big ) (t) +C \int _{t-T_1}^t r(\xi , a)\textrm{d}\xi +\frac{b}{a}\sup _{\xi \ge T}v(\xi ), \end{aligned}$$

here \(C=\Big (\Vert p\Vert _{BC} +\Vert r(\cdot , a)*q\Vert _{BC}\Big )\frac{ab}{a-b}\). Taking the supremum over \([2T_1,\infty )\), we have

$$\begin{aligned} \sup _{t\ge 2T_1} v(t) \le \sup _{t\ge 2T_1} \Big (p(t) + \big (r(\cdot , a)*q\big ) (t)\Big ) + \frac{C}{a}s(T_1,a) +\frac{b}{a}\sup _{\xi \ge T}v(\xi ). \end{aligned}$$

Let \(T\rightarrow \infty \), then \(T_1\rightarrow \infty \). So we obtain

$$\begin{aligned} \lim _{T_1\rightarrow \infty }\sup _{t\ge 2T_1} v(t)&\le \lim _{T_1\rightarrow \infty }\sup _{t\ge 2T_1} \Big (p(t) + \big (r(\cdot , a)*q\big ) (t)\Big )\\&\quad + \lim _{T_1\rightarrow \infty }\frac{C}{a}s(T_1,a) + \lim _{T\rightarrow \infty }\frac{b}{a}\sup _{\xi \ge T}v(\xi ). \end{aligned}$$

Hence, it implies

$$\begin{aligned} \limsup \limits _{t\rightarrow \infty } v(t) \le \Big (\limsup \limits _{t\rightarrow \infty } p(t)+\limsup \limits _{t\rightarrow \infty }\big (r(\cdot , a)*q\big ) (t)\Big )\dfrac{a}{a-b}. \end{aligned}$$

Consequently, the last statement in Proposition 2.4 holds. The proof is complete. \(\square \)

Corollary 2.5

If \(p\in BC_0\) and \(q(t)=q_0(t)+q_\infty (t),\; t\ge 0\), \(q_0\in BC_0, q_\infty \in BC({\mathbb {R}}^+)\) then there exits \(T(\epsilon )>0\), for each given \(\epsilon >0\), such that

$$\begin{aligned} v(t)\le \frac{\Vert q_\infty \Vert _{BC}}{a-b}+\epsilon ,\; t\ge T(\epsilon ). \end{aligned}$$

Halanay-type inequality plays an essential role in the stability analysis of nonlocal evolution equations. Another approach is combining the Lyapunov-Razumikhin method [9] and the nonlocal chain rule [17, Lemma 6.1]. We refer the readers interested in this approach to [28] for asymptotic stability result for a class of nonlinear Volterra integral-differential equations in the finite-dimensional case with the continuous kernel. A version of nonlinear Halanay-type inequality which utilizes the nonlinear structure should be more interesting in applications to nonlinear systems to obtain the optimal results.

2.4 Definition of mild solutions

For \(\varphi \in {\mathcal {B}}\), we define

$$\begin{aligned} {\textbf{C}}_\varphi =\{u\in C([0, T];H): u(0)=\varphi (0)\} \end{aligned}$$

as a closed subset of C([0, T]; H) with respect to the supremum norm denoted by \(\Vert \cdot \Vert _\infty \).

For any \(v\in {\textbf{C}}_\varphi \), the function \(v[\varphi ]:\mathbb R\rightarrow H\) is defined by

$$\begin{aligned} v[\varphi ](t) = {\left\{ \begin{array}{ll} \varphi (t), &{}\quad -\infty <t \le 0,\\ v(t), &{}\quad t >0. \end{array}\right. } \end{aligned}$$

Then, obviously

$$\begin{aligned} v[\varphi ]_t(\theta )= {\left\{ \begin{array}{ll} \varphi (t+\theta ), &{}\quad -\infty<\theta < -t,\\ v(t+\theta ), &{}\quad \theta \in [-t, 0]. \end{array}\right. } \end{aligned}$$

Motivated by arguments in [14], the definition of mild solution to the system (1.1)–(1.2) is given as follows.

Definition 2.1

A function \(u\in C((-\infty ,T]; H)\) is said to be a mild solution to (1.1)–(1.2) on \((-\infty ,T]\) iff \(u(t) = \varphi (t)\) for \(t\in (-\infty ,0]\) and

$$\begin{aligned} u(t) = S(t)\varphi (0) + \int _0^t R(t-\tau )f(\tau , u[\varphi ]_\tau ) \textrm{d}\tau , \end{aligned}$$

for \(t\in [0, T]\).

3 Existence results and dissipativity of solutions

We use the fixed point method to get our results by considering the operator defined by

$$\begin{aligned}&{\mathcal {F}}: {\textbf{C}}_\varphi \rightarrow {\textbf{C}}_\varphi \\&{\mathcal {F}}(v)(t) = S(t)\varphi (0) + \int _0^t R(t-\tau )f(\tau , v[\varphi ]_\tau ) \textrm{d}\tau ,\ t\in [0;T]. \end{aligned}$$

Obviously, if v is a fixed point of \({\mathcal {F}}\), then \(v[\varphi ]\) is a mild solution to (1.1)–(1.2). So \({\mathcal {F}}\) is referred to as the solution operator.

The first result is obtained in the case that f has a superlinear growth and the initial datum is sufficiently small.

Theorem 3.1

Let (A) and (K) hold. Suppose that the function f is continuous and satisfies the following estimate

$$\begin{aligned} \Vert f(t, w)\Vert \le \beta \vert w\vert _{{\mathcal {B}}} + \Psi (\vert w\vert _{{\mathcal {B}}}),\forall t\ge 0, w\in {\mathcal {B}}, \end{aligned}$$
(3.1)

where \(\beta > 0\), \(\Psi \in C({\mathbb {R}}^+;{\mathbb {R}})\) such that \(\lim \nolimits _{r\rightarrow 0}\frac{\Psi (r)}{r} =0\). If \(\beta <{\lambda _1} \big (\sup \nolimits _{s\in [0;T]}K(s)\big )^{-1}\), then there is a positive number \(\delta \) such that a mild solution to (1.1)–(1.2) exists globally provided \(|\varphi |_{\mathcal B}<\delta \). Furthermore, if f is locally Lipschitzian, i.e., for each \({\bar{r}}>0\), there is \(L({\bar{r}})>0\) such that

$$\begin{aligned} \Vert f(t,w_1)-f(t,w_2)\Vert \le L({\bar{r}}) \vert w_1-w_2\vert _{{\mathcal {B}}}, \end{aligned}$$
(3.2)

for all \(t\ge 0\), \( \vert w_i\vert _{{\mathcal {B}}}\le {\bar{r}}, i\in \{1,2\}\), then the mild solution to (1.1)–(1.2) is unique.

Proof

By definition of \({\mathcal {F}}\), we see that it is a continuous map from \({\textbf{C}}_\varphi \) into itself. We employ the Schauder theorem to prove that \({\mathcal {F}}\) has a fixed point in \({\textbf{C}}_\varphi \). Firstly, we find a number \(\eta >0\) such that \({\mathcal {F}}(B_\eta )\subset B_\eta \), provided that \(\vert \varphi \vert _{{\mathcal {B}}}\) is small enough. Here \(B_\eta =\{w\in \textbf{C}_\varphi \bigm | \sup _{t\in [0,T]}\Vert w(t)\Vert \le \eta \}\).

Due to the assumption on f, for \(\theta \in \big (0;\frac{\lambda _1}{K_T}-\beta \big )\), where \(K_T=\sup \nolimits _{[0;T]}K(s)\), there exists \({\bar{\eta }} >0\) such that

$$\begin{aligned} \Vert f(t,w)\Vert \le (\beta + \theta ) \vert w\vert _{\mathcal {B}}, \text { for all } w\in {\mathcal {B}},\ \vert w\vert _{\mathcal {B}} \le {\bar{\eta }}. \end{aligned}$$

Now we choose \(\eta =\frac{{\bar{\eta }}}{2K_T}\) and let \(\Vert u\Vert _\infty \le \eta \). If \(\vert \varphi \vert _{{\mathcal {B}}}\le \delta _1:=\frac{{\bar{\eta }}}{2M_T}\), here \(M_T=\sup \nolimits _{s\in [0; T]}M(s)\), then \(\vert u[\varphi ]_\tau \vert _{\mathcal {B}}\le {\bar{\eta }}\) for \(\tau >0\).

One gets

$$\begin{aligned} \Vert {\mathcal {F}}(u)(t)\Vert&\le s(t,\lambda _1)\Vert \varphi (0)\Vert + \int _0^t r(t-\tau , \lambda _1)(\beta + \theta ) \vert u[\varphi ]_\tau \vert _{\mathcal {B}}{\textrm{d}}\tau \\&\le s(t,\lambda _1) \Vert \varphi (0)\Vert \\&\quad + (\beta + \theta )\int _0^t r(t-\tau , \lambda _1)[K(\tau )\sup _{s\in [0; \tau ]}\Vert u(s)\Vert +M(\tau )\vert \varphi \vert _{\mathcal {B}}]\textrm{d}\tau \\&\le s(t,\lambda _1)\varrho \vert \varphi \vert _{\mathcal {B}}\\&\quad + (\beta + \theta ) \int _0^t r(t-\tau , \lambda _1)[K_T \eta + M_T\vert \varphi \vert _{\mathcal {B}}]\textrm{d}\tau . \end{aligned}$$

Using Proposition 2.1, we have

$$\begin{aligned} \Vert {\mathcal {F}}(u)(t)\Vert&\le s(t,\lambda _1)\varrho \vert \varphi \vert _{\mathcal {B}} + (\beta +\theta )\lambda _1^{-1}(1-s(t,\lambda _1))[K_T \eta + M_T\vert \varphi \vert _{\mathcal {B}}]\\&\le \varrho \vert \varphi \vert _{\mathcal {B}}+\frac{\beta +\theta }{\lambda _1}(K_T \eta + M_T\vert \varphi \vert _{\mathcal {B}}) \\&\le \varrho \vert \varphi \vert _{\mathcal {B}}+\frac{\beta +\theta }{\lambda _1}(K_T \eta + M_T\vert \varphi \vert _{\mathcal {B}})\\&=\bigg (\varrho +\frac{M_T(\beta +\theta )}{\lambda _1}\bigg )\vert \varphi \vert _{\mathcal {B}}+\frac{K_T(\beta +\theta )}{\lambda _1}\eta . \end{aligned}$$

Putting \(\delta _2:=\eta \frac{(\lambda _1-(\beta +\theta )K_T)}{\varrho \lambda _1+(\beta +\theta )M_T},\) we obtain \(\Vert {\mathcal {F}}(u)(t)\Vert \le \eta \) if \(|\varphi |_{\mathcal B}\le \delta _2\).

Thus \({\mathcal {F}}(B_\eta )\subset B_\eta \) if \(\vert \varphi \vert _{{\mathcal {B}}}< \delta :=\min \{\delta _1,\delta _2\}\). Employing Proposition 2.3, we see that \({\mathcal {F}}\) is compact. Therefore, by the Schauder theorem, the operator \(\mathcal F: B_\eta \rightarrow B_\eta \) possesses a fixed point. We gain the solvability of problem (1.1)–(1.2).

Finally, suppose that the Lipschitz condition (3.2) holds. If \(u_i, i\in \{1,2\}\), are solutions of (1.1)–(1.2), then

$$\begin{aligned} u_i(t) = S(t)\varphi (0) + \int _0^t R(t-\tau )f(\tau , u_i[\varphi ]_\tau )\textrm{d}\tau . \end{aligned}$$

Set \({\bar{r}} = \max \{\vert u_i[\varphi ]\vert _{{\mathcal {B}}}: i=1,2\}\). Then

$$\begin{aligned} \Vert u_1(t) - u_2(t)\Vert&\le \int _0^t r(t-\tau , \lambda _1)L({\bar{r}})\vert (u_1-u_2)[\varphi ]_\tau \vert _{{\mathcal {B}}} \textrm{d}\tau \\&\le L({\bar{r}}) \int _0^t r(t-\tau , \lambda _1)K_T\sup _{[0,\tau ]}\Vert u_1(\xi )-u_2(\xi )\Vert \textrm{d}\tau . \end{aligned}$$

Since the last term is nondecreasing with respect to t, we get

$$\begin{aligned} \sup _{[0,t]}\Vert u_1(\xi ) - u_2(\xi )\Vert \le L({\bar{r}}) \int _0^t r(t-\tau , \lambda _1)K_T\sup _{[0,\tau ]}\Vert u_1(\xi )-u_2(\xi )\Vert \textrm{d}\tau . \end{aligned}$$

Employing [14, Proposition 2.2], we conclude that \(u_1=u_2\). The proof is completed. \(\square \)

In the next result, we get a global existence to problem (1.1)–(1.2) by relaxing the smallness condition on both the initial datum and coefficients. However, the nonlinearity part must satisfy the sublinear condition.

Theorem 3.2

Assume the hypotheses (A) and (K). Let f be continuous and obey the condition given by

$$\begin{aligned} \Vert f(t,w)\Vert \le \alpha (t) + \beta \vert w\vert _{{\mathcal {B}}}, \forall t\ge 0, w\in {\mathcal {B}}, \end{aligned}$$

where \(\alpha \in L^1_{loc}({\mathbb {R}}^+;{\mathbb {R}}^+)\) and \(\beta \) is a nonnegative number. Then the problem (1.1)–(1.2) admits at least one global mild solution.

Proof

Since \({\mathcal {F}}\) is a compact operator, we just find a closed convex set which is invariant under the solution operator. On the other words, we construct a closed convex set \(D\subset \textbf{C}_\varphi \) such that \({\mathcal {F}}(D)\subset D\).

Indeed, from the formulation of \({\mathcal {F}}\), we obtain

$$\begin{aligned} \Vert {\mathcal {F}}(u)(t)\Vert&\le s(t,\lambda _1)\Vert \varphi (0)\Vert \\&\quad + \int _0^t r(t-\tau ,\lambda _1)\Big (\alpha (\tau ) + \beta \vert u[\varphi ]_\tau \vert _{{\mathcal {B}}}\Big )\textrm{d}\tau \\&\le s(t,\lambda _1)\Vert \varphi (0)\Vert + \int _0^t r(t-\tau ,\lambda _1) \alpha (\tau )\textrm{d}\tau \\&\quad + \int _0^t r(t-\tau ,\lambda _1)\beta \Big (K_T\sup \limits _{\xi \in [0; \tau ]}\Vert u(\xi )\Vert +M_T\vert \varphi \vert _{\mathcal B}\Big )\textrm{d}\tau ,\; t\in [0,T]. \end{aligned}$$

Then, in view of Proposition 2.1, we have

$$\begin{aligned} \Vert {\mathcal {F}}(u)(t)\Vert&\le s(t,\lambda _1)\Vert \varphi (0)\Vert + (r(\cdot ,\lambda _1)*\alpha ) (t) + \beta M_T\lambda _1^{-1}(1-s(t,\lambda _1))\vert \varphi \vert _{{\mathcal {B}}}\\&\quad +\beta K_T \int _0^t r(t-\tau ,\lambda _1)\sup _{[0,\tau ]}\Vert u(\xi )\Vert \textrm{d}\tau \\&\le (\varrho +\beta M_T\lambda _1^{-1})\vert \varphi \vert _{{\mathcal {B}}} + \sup _{[0,T]}(r(\cdot ,\lambda _1)*\alpha )(t) \\&\quad +\beta K_T \int _0^t r(t-\tau ,\lambda _1)\sup _{[0,\tau ]}\Vert u(\xi )\Vert \textrm{d}\tau ,\; t\in [0,T]. \end{aligned}$$

Because \(\tau \mapsto \sup \nolimits _{[0,\tau ]}\Vert u(\xi )\Vert \) is a nondecreasing function, the last integral is nondecreasing with respect to t. Therefore, one gets

$$\begin{aligned} \sup _{[0,t]}\Vert {\mathcal {F}}(u)(\xi )\Vert \le M_0 + \beta K_T \int _0^t r(t-\tau ,\lambda _1)\sup _{[0,\tau ]}\Vert u(\xi )\Vert \textrm{d}\tau ,\; t\in [0,T], \end{aligned}$$
(3.3)

where \(M_0 = (\varrho +\beta M_T\lambda _1^{-1})\vert \varphi \vert _{{\mathcal {B}}} + \sup \nolimits _{[0,T]}(r(\cdot ,\lambda _1)*\alpha )(t)\).

Let \(v\in C([0,T];{\mathbb {R}}^+)\) be the unique solution of the integral equation

$$\begin{aligned} v(t) = M_0 + \beta K_T \int _0^t r(t-\tau ,\lambda _1)v(\tau )\textrm{d}\tau , t\in [0,T]. \end{aligned}$$

We define the set

$$\begin{aligned} D=\left\{ w\in {\textbf{C}}_\varphi : \sup _{[0,t]}\Vert w(\xi )\Vert \le v(t), \forall t\in [0,T]\right\} . \end{aligned}$$

Obviously, D is a bounded closed convex set. Then, inequality (3.3) implies that \({\mathcal {F}}(D)\subset D\). The proof is completed. \(\square \)

The rest of this section is devoted to showing the dissipativity of the system. Let \({\mathbb {S}}(\varphi )\) be the solution set corresponding to a given initial datum \(\varphi \).

The problem (1.1)–(1.2) is said to be uniformly dissipative with an absorbing set \(B_\sigma \) if we can find a constant \(\sigma >0\) such that: For each bounded set \(D\subset {\mathcal {B}}\) there exists \(T(D)>0\) such that \(\forall u\in {\mathbb {S}}(\varphi ),\ \varphi \in D\), we have

$$\begin{aligned} \vert u_t\vert _{{\mathcal {B}}}\le \sigma ,\ \forall t>T(D). \end{aligned}$$

We now in a position to state a dissipativity result for (1.1)–(1.2).

Theorem 3.3

Let (A) and (K) hold. Suppose that f is a continuous function and satisfies the condition

$$\begin{aligned} \Vert f(t,w)\Vert \le \alpha (t) + \beta \vert w\vert _{{\mathcal {B}}}, \forall \; t\ge 0, w\in {\mathcal {B}}, \end{aligned}$$

where \(\beta >0\) such that \(\beta K_\infty <\lambda _1\), \(K_\infty =\sup \nolimits _{s\ge 0}K(s)\), \(\alpha \in L^1_{loc}(\mathbb R^+)\) is a nonnegative nondecreasing function such that \(r(\cdot , \lambda _1)*\alpha \in BC({\mathbb {R}}^+)\). If \(l\not \in L^1(\mathbb R^+)\) and \(M\in BC_0\), then the system (1.1)–(1.2) is dissipative with the absorbing set \(B_\sigma \) for any \(\sigma \) satisfying

$$\begin{aligned} \sigma >\frac{\lambda _1\alpha ^*K_\infty }{\lambda _1-\beta K_\infty }, \end{aligned}$$

where \(\alpha ^*=\sup \nolimits _{{\mathbb {R}}^+}(r(\cdot , \lambda _1)*\alpha )(t)\).

Proof

Let \(D\subset {\mathcal {B}}\) be a bounded set, \(\varphi \in D\) and \(u\in {\mathbb {S}}(\varphi )\). Then

$$\begin{aligned} u(t) = S(t)\varphi (0) + \int _0^t R(t-\tau )f(\tau , u[\varphi ]_\tau )\textrm{d}\tau , \; t\ge 0. \end{aligned}$$

Thus,

$$\begin{aligned} \Vert u(t)\Vert&\le s(t,\lambda _1)\Vert \varphi (0)\Vert + \int _0^t r(t-\tau ,\lambda _1)\big [\alpha (\tau ) + \beta \vert u[\varphi \big ]_\tau \vert ]\textrm{d}\tau \\&\le s(t,\lambda _1)\varrho \vert \varphi \vert _{{\mathcal {B}}} + \int _0^t r(t-\tau ,\lambda _1)\Big [\alpha (\tau ) + \beta M(\tau )\vert \varphi \vert _{{\mathcal {B}}}\\&\quad +\beta K_\infty \sup _{\xi \in [0; \tau ]}\Vert u(\xi )\Vert \Big ]\textrm{d}\tau \\&\le \Big (s(t,\lambda _1)\varrho +\beta \int _0^t r(t-\tau ,\lambda _1) M(\tau )\textrm{d}\tau \Big )\vert \varphi \vert _{{\mathcal {B}}}\\&\quad + \int _0^t r(t-\tau ,\lambda _1)\alpha (\tau )\textrm{d}\tau +\int _0^t r(t-\tau ,\lambda _1)\beta K_\infty \sup _{\xi \in [0; \tau ]}\Vert u(\xi )\Vert \textrm{d}\tau \\&\le \Big (\varrho +\frac{\beta M_\infty }{\lambda _1}\Big )\vert \varphi \vert _{{\mathcal {B}}}+ \int _0^t r(t-\tau ,\lambda _1)\alpha (\tau )\textrm{d}\tau +\frac{\beta K_\infty }{\lambda _1}\sup _{\xi \in [0;t]}\Vert u(\xi )\Vert . \end{aligned}$$

It implies

$$\begin{aligned} \sup _{\xi \in [0; t]}\Vert u(\xi )\Vert&\le \frac{\lambda _1}{\lambda _1-\beta K_\infty }\Big (\varrho +\frac{\beta M_\infty }{\lambda _1}\Big )\vert \varphi \vert _{{\mathcal {B}}}+ \frac{\lambda _1}{\lambda _1-\beta K_\infty }\sup \limits _{{\mathbb {R}}^+}(r(\cdot , \lambda _1)*\alpha )(t)\\&\le \frac{\lambda _1}{\lambda _1-\beta K_\infty }\Big (\varrho +\frac{\beta M_\infty }{\lambda _1}\Big )\vert D\vert _{{\mathcal {B}}}+ \frac{\lambda _1\alpha ^*}{\lambda _1-\beta K_\infty }, \end{aligned}$$

here \(\vert D\vert _{{\mathcal {B}}}:=\sup \{\vert w\vert _{{\mathcal {B}}}:\, w\in {\mathcal {B}}\}\) and \(\alpha ^*=\sup \nolimits _{{\mathbb {R}}^+}(r(\cdot , \lambda _1)*\alpha )(t)\).

Combing the last estimate and the formulation of solution, we have

$$\begin{aligned} \Vert u(t)\Vert&\le s(t,\lambda _1)\varrho \vert \varphi \vert _{{\mathcal {B}}}\\&\quad + \int _0^t r(t-\tau ,\lambda _1)\Big [\alpha (\tau ) + \beta M(\tau /2)\vert u_{\frac{\tau }{2}}\vert _{{\mathcal {B}}}+\beta K(\tau /2)\sup _{\xi \in [\tau /2; \tau ]}\Vert u(\xi )\Vert \Big ]\textrm{d}\tau \\&\le s(t,\lambda _1)\varrho \vert \varphi \vert _{{\mathcal {B}}} + \int _0^t r(t-\tau ,\lambda _1)\Big [\alpha (\tau ) + \beta M(\tau /2)\vert u_{\frac{\tau }{2}}\vert _{{\mathcal {B}}}\Big ]\textrm{d}\tau \\&\quad +\beta K_\infty \int _0^t r(t-\tau ,\lambda _1)\sup _{\xi \in [\tau /2; \tau ]}\Vert u(\xi )\Vert \textrm{d}\tau \\&\le s(t,\lambda _1)\varrho \vert D\vert _{{\mathcal {B}}}\\&\quad + \int _0^t r(t-\tau ,\lambda _1)\Big [\alpha (\tau ) + \beta M(\tau /2)\big (K_\infty K_D+M_\infty \vert D\vert _{{\mathcal {B}}}\big )\Big ]\textrm{d}\tau \\&\quad +\beta K_\infty \int _0^t r(t-\tau ,\lambda _1)\sup _{\xi \in [\tau /2; \tau ]}\Vert u(\xi )\Vert \textrm{d}\tau , \end{aligned}$$

where \(K_D=\frac{\lambda _1}{\lambda _1-\beta K_\infty }\Big (\varrho +\frac{\beta M_\infty }{\lambda _1}\Big )\vert D\vert _{{\mathcal {B}}}+ \frac{\lambda _1\alpha ^*}{\lambda _1-\beta K_\infty }\).

In view of Proposition 2.4 with \(v(t) = \Vert u(t)\Vert \), \(p(t)= s(t,\lambda _1)\varrho \vert D\vert _{{\mathcal {B}}}\), and \(q(t)=\alpha (t) + \beta \big (K_\infty K_D+M_\infty \vert D\vert _{{\mathcal {B}}}\big )M(t/2)\), we have \(\Vert u(\cdot )\Vert \in BC({\mathbb {R}}^+)\) and

$$\begin{aligned} \limsup _{t\rightarrow \infty }\Vert u(t)\Vert&\le \Big [\limsup _{t\rightarrow \infty }s(t,\lambda _1)\varrho \vert D\vert _{{\mathcal {B}}}+\limsup _{t\rightarrow \infty }\big (r(\cdot , \lambda _1)*\alpha \big )(t)\Big ]\frac{\lambda _1}{\lambda _1-\beta K_\infty }\\&\quad + \limsup _{t\rightarrow \infty }\Big [r(\cdot , \lambda _1)*M\big (\frac{\cdot }{2}\big )(t)\Big ]\beta \big (K_\infty K_D+M_\infty \vert D\vert _{{\mathcal {B}}}\big ) \frac{\lambda _1}{\lambda _1-\beta K_\infty }\\&\le \frac{\lambda _1\alpha ^*}{\lambda _1-\beta K_\infty }, \end{aligned}$$

thanks to the fact that \(M\big (\frac{\cdot }{2}\big )\in BC_0\). So for \(\epsilon >0\) there exists \(T_1(\epsilon )>0\) such that

$$\begin{aligned} \sup _{\xi \ge t}\Vert u(\xi )\Vert \le \frac{\lambda _1\alpha ^*}{\lambda _1-\beta K_\infty }+\frac{\epsilon }{2K_\infty },\; \forall t\ge T_1(\epsilon ). \end{aligned}$$

Thus,

$$\begin{aligned} \vert u_t\vert _{{\mathcal {B}}}&\le K_\infty \Big (\frac{\lambda _1\alpha ^*}{\lambda _1-\beta K_\infty }+\frac{\epsilon }{2K_\infty }\Big )+M\Big (\frac{t}{2}\Big )\vert u_{\frac{t}{2}}\vert _{{\mathcal {B}}},\; \forall t\ge 2T_1(\epsilon ). \end{aligned}$$
(3.4)

On the other hand, we get

$$\begin{aligned} M\Big (\frac{t}{2}\Big )\vert u_{\frac{t}{2}}\vert _{{\mathcal {B}}}\le M\Big (\frac{t}{2}\Big )\big (K_\infty K_D+M_\infty \vert D\vert _{{\mathcal {B}}}\big ). \end{aligned}$$

By virtue of \(M\in BC_0\), there exists \(T_2(D,\epsilon )>0\) such that

$$\begin{aligned} M\Big (\frac{t}{2}\Big )\vert u_{\frac{t}{2}}\vert _{{\mathcal {B}}}\le \frac{\epsilon }{2},\quad \forall t\ge T_2(D,\epsilon ). \end{aligned}$$
(3.5)

From (3.4) and (3.5), we arrive at

$$\begin{aligned} \vert u_t\vert _{{\mathcal {B}}}&\le \frac{\lambda _1\alpha ^*K_\infty }{\lambda _1-\beta K_\infty }+\epsilon ,\; \forall t\ge T(D,\epsilon ), \end{aligned}$$

where \(T(D,\epsilon )=\max \{T_1(\epsilon ), T_2(D,\epsilon )\}\). We choose a sufficiently small number \(\epsilon \) to get the uniform dissipativity with any \(\sigma > \frac{\lambda _1\alpha ^*K_\infty }{\lambda _1-\beta K_\infty }\). The proof is completed. \(\square \)

4 Asymptotic stability and weakly asymptotic stability

In this section, we utilize the well-known Lyapunov stability theory [9] to nonlocal evolution equations involving infinite delays. Note that the Lyapunov stability theory is also a basic tool to analyze other general systems, for instance, fractional with impulsive effects [12, 13], fractal differential systems [27] or Volterra integral-differential systems [28]. We will establish this asymptotic (weak) stability for the system with (without) the uniqueness, respectively.

4.1 Asymptotic stability

In the following theorem, we prove the asymptotic stability of solution to (1.1)–(1.2) when the nonlinearity is globally Lipschitzian.

Theorem 4.1

Let (A) and (K) hold. Assume that f satisfies the Lipschitz condition

$$\begin{aligned} \Vert f(t, w_1)-f(t,w_2)\Vert \le \beta \vert w_1-w_2\vert _{{\mathcal {B}}}, \forall \; t\ge 0, w_1,w_2\in {\mathcal {B}}, \end{aligned}$$

where \(\beta >0\) such that \(\beta K_\infty <\lambda _1\). If \(l\not \in L^1({\mathbb {R}}^+)\) and \(M\in BC_0\), then an arbitrary solution of (1.1)–(1.2) is asymptotically stable.

Proof

Let \(u(\cdot ,\varphi )\) and \(v(\cdot ,\psi )\) be solutions of (1.1)–(1.2) with initial data \(\varphi \) and \(\psi \), respectively. Then

$$\begin{aligned} \Vert u(t)-v(t)\Vert&\le s(t,\lambda _1)\Vert \varphi (0)-\psi (0)\Vert \\&\quad + \int _0^t r(t-\tau ,\lambda _1)\Vert f(\tau ,u[\varphi ]_\tau ) - f(\tau ,v[\psi ]_\tau )\Vert \textrm{d}\tau \\&\le s(t,\lambda _1)\Vert \varphi (0)-\psi (0)\Vert \\&\quad + \int _0^t r(t-\tau ,\lambda _1)\beta \vert u[\varphi ]_\tau - v[\psi ]_\tau \vert _{{\mathcal {B}}} \textrm{d}\tau \\&\le s(t,\lambda _1)\Vert \varphi (0)-\psi (0)\Vert \\&\quad + \beta \int _0^t r(t-\tau ,\lambda _1)\big [K_\infty \sup _{\xi \in [0;\tau ]}\Vert u(\xi ) - v(\xi )\Vert +M_\infty \vert \varphi -\psi \vert _{{\mathcal {B}}}\big ]\textrm{d}\tau \\&\le \frac{\beta K_\infty }{\lambda _1}\sup _{\xi \in [0;t]}\Vert u(\xi ) - v(\xi )\Vert +\Big (\varrho +\frac{\beta M_\infty }{\lambda _1}\Big )\vert \varphi -\psi \vert _{{\mathcal {B}}}. \end{aligned}$$

Therefore

$$\begin{aligned} \sup _{\xi \in [0;t]}\Vert u(\xi ) - v(\xi )\Vert \le \frac{\varrho \lambda _1+\beta M_\infty }{\lambda _1-\beta K_\infty }\vert \varphi -\psi \vert _{{\mathcal {B}}}. \end{aligned}$$
(4.1)

Using (B3) and the estimate above, one gets

$$\begin{aligned} \vert u_t-v_t\vert _{{\mathcal {B}}}&\le K(t)\sup _{\xi \in [0;t]}\Vert u(\xi ) - v(\xi )\Vert + M(t)\vert \varphi -\psi \vert _{{\mathcal {B}}}\nonumber \\&\le \left( K_\infty \frac{\varrho \lambda _1+\beta M_\infty }{\lambda _1-\beta K_\infty }+ M_\infty \right) \vert \varphi -\psi \vert _{{\mathcal {B}}},\ \forall t\ge 0. \end{aligned}$$
(4.2)

Thus,

$$\begin{aligned} \Vert u(t)-v(t)\Vert&\le s(t,\lambda _1)\Vert \varphi (0)-\psi (0)\Vert + \beta \int _0^t r(t-\tau ,\lambda _1)M(\tau /2)\vert u_{\frac{\tau }{2}}-v_{\frac{\tau }{2}}\vert _{{\mathcal {B}}}\textrm{d}\tau \\&\quad + \beta \int _0^t r(t-\tau ,\lambda _1)K(\tau /2)\sup _{\xi \in [\tau /2;\tau ]}\Vert u(\xi ) - v(\xi )\Vert \textrm{d}\tau \\&\le s(t,\lambda _1)\Vert \varphi (0)-\psi (0)\Vert \\&\quad + \beta (K_\infty \frac{\varrho \lambda _1+\beta M_\infty }{\lambda _1-\beta K_\infty }+ M_\infty )\vert \varphi -\psi \vert _{{\mathcal {B}}}\int _0^t r(t-\tau ,\lambda _1)M(\tau /2)\textrm{d}\tau \\&\quad + \beta K_\infty \int _0^t r(t-\tau ,\lambda _1)\sup _{\xi \in [\tau /2;\tau ]}\Vert u(\xi ) - v(\xi )\Vert \textrm{d}\tau \end{aligned}$$

By Proposition 2.4, we have

$$\begin{aligned} \limsup _{t\rightarrow \infty }\Vert u(t)-v(t)\Vert&\le \frac{\lambda _1}{\lambda _1-\beta K_\infty }\limsup _{t\rightarrow \infty }s(t,\lambda _1)\Vert \varphi (0)-\psi (0)\Vert \\&\quad +C\limsup _{t\rightarrow \infty }\big (r(\cdot ,\lambda _1)*M(\cdot /2)\big )(t), \end{aligned}$$

here \(C=\beta (K_\infty \frac{\varrho \lambda _1+\beta M_\infty }{\lambda _1-\beta K_\infty }+ M_\infty )\vert \varphi -\psi \vert _{{\mathcal {B}}}\). Then

$$\begin{aligned} \limsup _{t\rightarrow \infty }\Vert u(t)-v(t)\Vert =0, \end{aligned}$$

thanks to \(M\in BC_0\).

It follows that

$$\begin{aligned} \forall \epsilon>0, \; \exists \ T_1(\epsilon )>0: \sup _{\xi \ge t}\Vert u(\xi )-v(\xi )\Vert \le \frac{\epsilon }{2K_\infty },\quad \forall t\ge T_1(\epsilon ). \end{aligned}$$

Consequently,

$$\begin{aligned} \vert u_t-v_t\vert _{{\mathcal {B}}}&\le K_\infty \frac{\epsilon }{2K_\infty }+ \frac{\varrho \lambda _1+\beta M_\infty }{\lambda _1-\beta K_\infty }\vert \varphi -\psi \vert _{\mathcal B}M(t/2),\ \forall t\ge 2T_1(\epsilon ), \end{aligned}$$

due to (4.1). Since \(M\in BC_0\), there exists \(T_2>0\) such that

$$\begin{aligned} \frac{\varrho \lambda _1+\beta M_\infty }{\lambda _1-\beta K_\infty }\vert \varphi -\psi \vert _{{\mathcal {B}}}M(t/2)\le \frac{\epsilon }{2},\ \forall t\ge T_2. \end{aligned}$$

This gives

$$\begin{aligned} \vert u_t-v_t\vert _{{\mathcal {B}}}&\le \frac{\epsilon }{2}+ \frac{\epsilon }{2}=\epsilon ,\ \forall t\ge T, \end{aligned}$$
(4.3)

here \(T=\max \{2T_1(\epsilon ),T_2\}\).

Combining (4.2) and (4.3) gives us the desired conclusion. \(\square \)

The next theorem states the asymptotic stability of the zero solution when f satisfies the hypotheses in Theorem 3.1 with \(K_\infty \) in place of \(K_T\).

Theorem 4.2

Let the hypotheses of Theorem 3.1 hold where \(K_T\) is replaced by \(K_\infty \). If \(l\not \in L^1({\mathbb {R}}^+)\) and \(M\in BC_0\), then the zero solution of (1.1) is asymptotically stable.

Proof

Choose the numbers \(\theta \in (0, \frac{\lambda _1}{K_\infty }-\beta )\), \(\eta \) and \(\delta \) as in the proof of Theorem 3.1. Combining (3.1)–(3.2) and \(\Vert \varphi \Vert _\infty <\delta \), problem (1.1)–(1.2) possesses a unique solution \(u\in B_\eta \). Moreover, this solution verifies the following

$$\begin{aligned} \Vert u(t)\Vert&\le s(t,\lambda _1)\Vert \varphi (0)\Vert + \int _0^t r(t-\tau , \lambda _1)(\beta + \theta ) \vert u[\varphi ]_\tau \vert _{\mathcal {B}}{\textrm{d}}\tau \\&\le s(t,\lambda _1) \Vert \varphi (0)\Vert \\&\quad + (\beta + \theta )\int _0^t r(t-\tau , \lambda _1)[K_\infty \sup _{s\in [0; \tau ]}\Vert u(s)\Vert +M(\tau )\vert \varphi \vert _{\mathcal {B}}]\textrm{d}\tau \\&\le \frac{(\beta +\theta )K_\infty }{\lambda _1}\sup _{s\in [0; t]}\Vert u(s)\Vert +\Big (\varrho + (\beta + \theta )\int _0^t r(t-\tau , \lambda _1)M(\tau )\textrm{d}\tau \Big )\vert \varphi \vert _{\mathcal {B}}, \end{aligned}$$

for all \(t\ge 0\). Then

$$\begin{aligned} \sup \limits _{s\in [0; t]}\Vert u(s)\Vert&\le \frac{\lambda _1}{\lambda _1-(\beta +\theta )K_\infty }\Big (\varrho + (\beta + \theta )M^*\Big )\vert \varphi \vert _{\mathcal {B}}, \end{aligned}$$

for all \(t\ge 0\), where \(M^*=\sup \nolimits _{t\ge 0}\int _0^t r(t-\tau , \lambda _1)M(\tau )\textrm{d}\tau \).

From the last estimate and (B3), we see that

$$\begin{aligned} \vert u_t\vert _{{\mathcal {B}}}\le \Bigg (\frac{\lambda _1K_\infty \big (\varrho + (\beta + \theta )M^*\big )}{\lambda _1-(\beta +\theta )K_\infty }+M_\infty \Bigg )\vert \varphi \vert _{\mathcal {B}}. \end{aligned}$$
(4.4)

By the same arguments as in Theorem 4.1, one gets

$$\begin{aligned} \limsup _{t\rightarrow \infty }\Vert u(t)\Vert =0. \end{aligned}$$

Then

$$\begin{aligned} \lim \limits _{t\rightarrow \infty } \vert u_t\vert _{{\mathcal {B}}}=0. \end{aligned}$$
(4.5)

From (4.4) and (4.5), we obtain the asymptotic stability of the zero solution.

\(\square \)

4.2 Weakly asymptotic stability

In this subsection, we do not assume that f is Lipschitz continuous. Consequently, the solutions of problem (1.1)–(1.2) are not necessarily unique. We aim at the weakly asymptotic stability for the zero solution.

Definition 4.1

[3] Let \({\mathbb {S}}(\varphi )\) be the solution set of (1.1)–(1.2) with respect to the initial datum \(\varphi \). Assume that \(0\in {\mathbb {S}}(0)\), that is (1.1) admits zero solution. The zero solution of (1.1) is said to be weakly asymptotically stable iff

  1. (1)

    It is stable, i.e. for every \(\varepsilon >0\) there exists \(\delta >0\) such that if \(|\varphi |_{{\mathcal {B}}}<\delta \) then \(|u_t|_{{\mathcal {B}}}<\varepsilon \) for all \(u\in {\mathbb {S}}(\varphi )\);

  2. (2)

    It is weakly attractive, i.e. for each \(\varphi \in {\mathcal {B}}\), there exists \(u\in {\mathbb {S}}(\varphi )\) such that \(|u_t|_{{\mathcal {B}}}\rightarrow 0\) as \(t\rightarrow \infty \).

In the present situation, we employ a version of fixed point theory for condensing maps. We now collect some essential properties of measure of noncompactness (MNC), and fixed point principles.

Definition 4.2

[11] Let E be a Banach space and \({\mathcal {B}}(E)\) the collection of all nonempty and bounded subsets of E. A function \(\omega : \mathcal B(E)\rightarrow {\mathbb {R}}^+\) is said to be a measure of noncompactness (MNC) if \(\omega (\overline{\textrm{co}}\,D)=\omega (D)\) for all \(D\in {\mathcal {B}}(E)\). An MNC is called

  • nonsingular if \(\omega (D\cup \{x\}) = \omega (D)\) for all \(D\in {\mathcal {B}}(E)\), \(x\in E\).

  • monotone if \(\omega (D_1)\le \omega (D_2)\) provided that \(D_1\subset D_2\).

The Hausdorff measure of noncompactness is an MNC which is defined by

$$\begin{aligned} \chi (D) = \inf \{\varepsilon >0: D\text { admits a finite }\varepsilon -\text {net}\}. \end{aligned}$$

Definition 4.3

[11] Let E be a Banach space and \(D\in {\mathcal {B}}(E)\). A continuous map \({\mathcal {F}}: D\rightarrow E\) is said to be condensing with respect to MNC \(\omega \) (\(\omega \)-condensing) iff the relation \(\omega (B)\le \omega ({\mathcal {F}}(B)), B\subset D\), implies that B is relatively compact.

The following theorem states a fixed point principle for condensing maps.

Theorem 4.3

[11] Let \(\omega \) be a monotone and nonsingular MNC on E. Assume that \(D\subset E\) is a closed convex set and \({\mathcal {F}}:D\rightarrow D\) is \(\omega \)-condensing. Then \({\mathcal {F}}\) admits a fixed point.

In this subsection, we consider the solution operator on \(BC_0({\mathbb {R}}^+;H)\) where

$$\begin{aligned} BC_0({\mathbb {R}}^+;H)=\{y\in BC({\mathbb {R}}^+;H) : \lim _{t\rightarrow \infty }\Vert y(t)\Vert =0\}. \end{aligned}$$

It is known that \(BC_0({\mathbb {R}}^+;H)\) is a closed subspace of \(BC({\mathbb {R}}^+;H)\). Given \(\varphi \in {\mathcal {B}}\), put \({{\mathcal {B}}}{{\mathcal {C}}}_0^\varphi =\{u\in BC_0({\mathbb {R}}^+;H): u(0)=\varphi (0)\}\). Then \({{\mathcal {B}}}{{\mathcal {C}}}_0^\varphi \) is a closed convex set of \(BC_0({\mathbb {R}}^+;H)\).

Let \(\pi _T: {{\mathcal {B}}}{{\mathcal {C}}}_0^\varphi \rightarrow C([0,T];H)\) the restriction operator on \({{\mathcal {B}}}{{\mathcal {C}}}_0^\varphi \), which is defined by \(\pi _T(u)(t)=u(t), \forall \, t\in [0,T]\), for all \(u\in {{\mathcal {B}}}{{\mathcal {C}}}_0^\varphi \). For a bounded set D in \({{\mathcal {B}}}{{\mathcal {C}}}_0^\varphi \), we set

$$\begin{aligned} d_\infty (D)&= \lim _{T\rightarrow \infty }\sup _{u\in D}\sup _{t\ge T}\Vert u(t)\Vert ,\\ \chi _\infty (D)&= \sup _{T>0}\chi _T(D), \end{aligned}$$

where \(\chi _T(\cdot )\) is the Hausdorff MNC in C([0, T]; H). Put

$$\begin{aligned} \chi ^*(D) = d_\infty (D) + \chi _\infty (D). \end{aligned}$$

It is shown in [2] that \(\chi ^*\) satisfies all properties stated in Definition 4.2. In addition, if \(\chi ^*(D)=0\), then D is relatively compact in \(BC_0({\mathbb {R}}^+;H)\). Especially, if \(u\in C({\mathbb {R}}^+;H)\), then \(d_\infty (\{u\})=0\) if and only if \(u\in BC_0({\mathbb {R}}^+;H)\).

We are now in a position to present the main result in this section.

Theorem 4.4

Assume (A) and (K) hold. Let the nonlinear f be continuous and satisfy the estimate

$$\begin{aligned} \Vert f(t,w)\Vert \le \beta (t)\vert w\vert _{{\mathcal {B}}}, \; \forall t\ge 0, w\in {\mathcal {B}}, \end{aligned}$$
(4.6)

where \(\beta \in BC({\mathbb {R}}^+)\) is a nonnegative function. Suppose that \(l\not \in L^1({\mathbb {R}}^+)\), \(K\in BC({\mathbb {R}}^+)\) and \(M\in BC_0\). Then the zero solution of (1.1) is weakly asymptotically stable provided that

$$\begin{aligned} \ell =\limsup _{t\rightarrow \infty }\int _{t/2}^t r(t-\tau ,\lambda _1)\beta (\tau )K(\tau /2)\textrm{d}\tau <1. \end{aligned}$$
(4.7)

Let us outline the proof. The idea is employing the fixed point theorem for condensing maps. We first establish the well-defined and condensing property of the solution operator in Lemma 4.5. Then Lemma 4.6 reduces the condition on functions K and M to the auxiliary functions \(K_1\) and \(M_1\). Using this preparation, Lemma 4.7 constructs a closed bounded invariant subset of the solution operator. Combining all these results, the poof is finished by following the standard argument. We are now in a position to show the proof in details.

Lemma 4.5

Assume the hypotheses of Theorem 4.4. Then

$$\begin{aligned} d_\infty ({\mathcal {F}}(D))\le \ell \cdot d_\infty (D) \end{aligned}$$

for all bounded set \(D\subset {{\mathcal {B}}}{{\mathcal {C}}}_0^\varphi \). In particular, \({\mathcal {F}}({{\mathcal {B}}}{{\mathcal {C}}}_0^\varphi )\subset {{\mathcal {B}}}{{\mathcal {C}}}_0^\varphi \).

Proof

We first show that

$$\begin{aligned} \limsup _{t\rightarrow +\infty }\int _0^{t} r(t-\tau ,\lambda _1)M(\tau /2)\beta (\tau )\textrm{d}\tau = 0. \end{aligned}$$
(4.8)

Indeed, we see that

$$\begin{aligned} \int _0^{t} r(t-\tau ,\lambda _1)M(\tau /2)\beta (\tau )\textrm{d}\tau&\le M_\infty \beta _\infty \int _0^{t/2} r(t-\tau ,\lambda _1)\textrm{d}\tau \\&\quad + \beta _\infty \int _{t/2}^t r(t-\tau ,\lambda _1)M(\tau /2)\textrm{d}\tau , \end{aligned}$$

where \(M_\infty = \sup _{t\ge 0}M(t)\) and \(\beta _\infty = \sup _{t\ge 0}\beta (t)\). Moreover,

$$\begin{aligned} \int _0^{t/2} r(t-\tau ,\lambda _1)\textrm{d}\tau = \int _{t/2}^t r(\tau ,\lambda _1)\textrm{d}\tau \rightarrow 0\text { as } t\rightarrow \infty , \end{aligned}$$

according to \(r(\cdot ,\lambda _1)\in L^1({\mathbb {R}}^+)\). In addition,

$$\begin{aligned} \int _{t/2}^t r(t-\tau ,\lambda _1)M(\tau /2)\textrm{d}\tau&\le \sup _{\tau \ge t/4}M(\tau )\int _0^{t/2}r(\tau ,\lambda _1)\textrm{d}\tau \\&\le \lambda _1^{-1}\sup _{\tau \ge t/4}M(\tau )\rightarrow 0\text { as } t\rightarrow \infty , \end{aligned}$$

thanks to the assumption \(M\in BC_0\). Thus, (4.8) takes place.

Now let \(D\subset {{\mathcal {B}}}{{\mathcal {C}}}_0^\varphi \) be a bounded set and \(u\in D\). Put \(R_D=\sup \nolimits _{u\in D} \Vert u\Vert _{BC}+\vert \varphi \vert _{{\mathcal {B}}}\). Then

$$\begin{aligned} \Vert {\mathcal {F}}(u)(t)\Vert&\le s(t,\lambda _1)\Vert \varphi (0)\Vert +\int _0^t r(t-\tau ,\lambda _1)\beta (\tau )\vert u[\varphi ]_\tau \vert _{{\mathcal {B}}}\textrm{d}\tau \nonumber \\&\le s(t,\lambda _1)\Vert \varphi (0)\Vert \quad \nonumber \\&\quad +\int _0^t r(t-\tau ,\lambda _1)\beta (\tau )\left( M(\tau /2)\vert u[\varphi ]_{\tau /2}\vert _{{\mathcal {B}}}+K(\tau /2)\sup _{\xi \in [\tau /2,\tau ]}\Vert u(\xi )\Vert \right) \textrm{d}\tau \nonumber \\&\le s(t,\lambda _1)\Vert \varphi (0)\Vert \quad \nonumber \\&\quad + r*{\widetilde{M}}(t)[M_\infty \vert \varphi \vert _{\mathcal B}+K_\infty R_D]+\int _0^t r(t-\tau ,\lambda _1){\widetilde{K}}(\tau )\sup _{\xi \in [\tau /2,\tau ]}\Vert u(\xi )\Vert \textrm{d}\tau , \end{aligned}$$
(4.9)

for all \(t\ge 0\), where \({\widetilde{M}}(\tau )=\beta (\tau )M(\tau /2), {\widetilde{K}}(\tau )=\beta (\tau )K(\tau /2)\).

In order to estimate the last term, fixing a \(T>0\), for \(t>4T\), we get

$$\begin{aligned} \int _0^t r(t-\tau ,\lambda _1){\widetilde{K}}(\tau )\sup _{\xi \in [\tau /2,\tau ]}\Vert u(\xi )\Vert \textrm{d}\tau&\le R_D {\widetilde{K}}_\infty \int _0^{t/2}r(t-\tau ,\lambda _1)\textrm{d}\tau \nonumber \\&\quad +\sup _{\xi \ge T}\Vert u(\xi )\Vert \int _{t/2}^{t}r(t-\tau ,\lambda _1){\widetilde{K}}(\tau )\textrm{d}\tau . \end{aligned}$$
(4.10)

Combining (4.9) and (4.10) yields

$$\begin{aligned} \sup _{u\in D}\sup _{t\ge 4T}\Vert {\mathcal {F}}(u)(t)\Vert&\le \sup _{t\ge 4T}s(t,\lambda _1)\Vert \varphi (0)\Vert \\&\quad +\sup _{t\ge 4T}\left( r*{\widetilde{M}}(t)(M_\infty \vert \varphi \vert _{{\mathcal {B}}}+K_\infty R_D\right. )\\&\quad \left. +R_D{\widetilde{K}}_\infty \frac{s(t/2,\lambda _1)-s(t,\lambda _1)}{\lambda _1} \right) \\&\quad + \left( \sup _{u\in D}\sup _{\xi \ge T}\Vert u(\xi )\Vert \right) \sup _{t\ge 4T} \int _{t/2}^t r(t-\tau ,\lambda _1) {\widetilde{K}}(\tau )\textrm{d}\tau . \end{aligned}$$

Letting \(T\rightarrow \infty \), we conclude

$$\begin{aligned} d_\infty (\Phi (D)) \le \ell \cdot d_\infty (D), \end{aligned}$$

thanks to (4.7)–(4.8) and

$$\begin{aligned} \sup \limits _{t\ge 4T}s(t,\lambda _1)= s(4T,\lambda _1)\rightarrow 0\text { as } T\rightarrow \infty . \end{aligned}$$

Consequently, if \(D=\{u\}\) then \(d_\infty (\{{\mathcal {F}}(u)\})\le \ell \cdot d_\infty (\{u\}) = 0\). This yields \({\mathcal {F}}(u)\in {{\mathcal {B}}}{{\mathcal {C}}}_0^\varphi \) for all \(u\in {{\mathcal {B}}}{{\mathcal {C}}}_0^\varphi \). It follows that \({\mathcal {F}}({{\mathcal {B}}}{{\mathcal {C}}}_0^\varphi )\subset {{\mathcal {B}}}{{\mathcal {C}}}_0^\varphi \). \(\square \)

Lemma 4.6

Assume that (4.7) is satisfied. Let \(K_1(t)=K(t/2)+K(t/2)M(t/2)\). Then, there exist two positive numbers \(T_1>0\) and \(l_1<1\) such that \( r(\cdot ,\lambda _1)*(\beta K_1)(t)\le l_1\) for all \(t\ge T_1\).

Proof

We get

$$\begin{aligned} r(\cdot ,\lambda _1)* (\beta K_1)(t)&=\int _0^t r(t-\tau ,\lambda _1)\beta (\tau )K(\tau /2)\textrm{d}\tau \\&\quad +\int _0^tr(t-\tau ,\lambda _1)\beta (\tau )K(\tau /2)M(\tau /2)\textrm{d}\tau \\&\le \int _0^{t/2}r(t-\tau ,\lambda _1)\beta (\tau /2)K(\tau /2)\textrm{d}\tau \\&\quad +\int _{t/2}^t r(t-\tau ,\lambda _1)\beta (\tau )K(\tau /2)\textrm{d}\tau \\&\quad +\int _0^tr(t-\tau ,\lambda _1)\beta (\tau )K(\tau /2)M(\tau /2)\textrm{d}\tau \\&\le K_\infty \beta _\infty \int _{t/2}^t r(\tau ,\lambda _1)\textrm{d}\tau +\int _{t/2}^t r(t-\tau ,\lambda _1)\beta (\tau )K(\tau /2)\textrm{d}\tau \\&\quad +K_\infty \int _0^tr(t-\tau ,\lambda _1)\beta (\tau )M(\tau /2)\textrm{d}\tau . \end{aligned}$$

Obviously, the first term tends to zero when \(t\rightarrow \infty \) thanks to \(r\in L^1({\mathbb {R}}^+)\). The last term goes to zero by (4.8). Thus, it follows from (4.7) that

$$\begin{aligned} \limsup _{t\rightarrow \infty }r(\cdot ,\lambda _1)*(\beta K_1)(t)=\limsup _{t\rightarrow \infty }\int _{t/2}^tr(t-\tau , \lambda _1)\beta (\tau )K(\tau /2)=l<1. \end{aligned}$$

The last inequality implies the desired result. \(\square \)

Lemma 4.7

Assume the hypotheses of Theorem 4.4. Then, there exists a bounded closed convex set which is invariant under the solution operator.

Proof

Take \(T_1\) and \(l_1\) from Lemma 4.6, that is,

$$\begin{aligned} r(\cdot ,\lambda _1)*(\beta K_1)(t)\le l_1,\quad \forall t\ge T_1. \end{aligned}$$

The construction of the invariant set consists of two steps. We first use a suitable weight function to obtain the invariant set for finite time. Then we combine the estimate on this finite time interval with Lemma 4.6 to get the estimate for large time, which gives us the invariant set for all time.

Step 1 (Estimate on the interval \([0,T_1]\)). We have

$$\begin{aligned}&\int _0^tr(t-\tau ,\lambda _1)\beta (\tau )K_1(\tau )e^{-\mu (t-\tau )}\textrm{d}\tau \\&\quad \le \Vert \beta K_1\Vert _{L^\infty (0,T_1)}\int _0^tr(t-\tau ,\lambda _1)e^{-\mu (t-\tau )}\textrm{d}\tau \\&\quad \le \Vert \beta K_1\Vert _{L^\infty (0,T_1)}\int _0^{T_1}r(\tau ,\lambda _1)e^{-\mu \tau }\textrm{d}\tau ,\forall t\in (0,T_1]. \end{aligned}$$

Observing that

$$\begin{aligned} \lim _{\mu \rightarrow +\infty }\int _0^{T_1}r(\tau ,\lambda _1)e^{-\mu \tau }\textrm{d}\tau =0, \end{aligned}$$

one can take a positive number \(\mu \) such that

$$\begin{aligned} r(\cdot ,\lambda _1)*(\beta K_1m)(t)<\frac{m(t)}{2}, \text { for all }t\in [0,T_1], \end{aligned}$$
(4.11)

where \(m(t)=e^{-\mu t}\). Let \(M_1(t) = M(t/2)^2\), then one sees that

$$\begin{aligned} \vert u_t\vert _{{\mathcal {B}}}&\le K(t/2)\sup _{\xi \in [t/2,t]}\Vert u(\xi )\Vert +M(t/2)\vert u_{t/2}\vert _{{\mathcal {B}}}\nonumber \\&\le K(t/2)\sup _{\xi \in [t/2,t]}\Vert u(\xi )\Vert +M(t/2)\left( K(t/2)\sup _{\xi \in [0,t/2]}\Vert u(\xi )\Vert +M(t/2)\vert \varphi \vert _{{\mathcal {B}}}\right) \nonumber \\&\le K_1(t)\sup _{\xi \in [0,t]}\Vert u(\xi )\Vert + M_1(t)\vert \varphi \vert _{{\mathcal {B}}}, \end{aligned}$$
(4.12)

according to the axiom (B3) of phase spaces.

Choose

$$\begin{aligned} R_1\ge 2\sup \limits _{t\in [0,T_1]}\dfrac{(\varrho +\Vert r(\cdot ,\lambda _1)*(\beta M_1)\Vert _\infty )\vert \varphi \vert _{{\mathcal {B}}}}{m(t)}. \end{aligned}$$
(4.13)

Then for all \(u\in BC_0({\mathbb {R}}^+; H)\) such that \(\sup \nolimits _{t\in [0,T_1]}\dfrac{\Vert u(t)\Vert }{m(t)}\le R_1\), one has

$$\begin{aligned} \Vert {\mathcal {F}}(u)(t)\Vert&\le s(t,\lambda _1)\Vert \varphi (0)\Vert + \int _0^t r(t-\tau ,\lambda _1)\beta (\tau )\vert u[\varphi ]_\tau \vert _{{\mathcal {B}}}\textrm{d}\tau \\&\le \Vert \varphi (0)\Vert + R_1 \int _0^t r(t-\tau ,\lambda _1)\beta (\tau )K_1(\tau )m(\tau ) \textrm{d}\tau \\&\quad + \vert \varphi \vert _{{\mathcal {B}}} \int _0^t r(t-\tau ,\lambda _1) \beta (\tau )M_1(\tau )\textrm{d}\tau \\&\le \left( \varrho +\Vert r(\cdot ,\lambda _1)*(\beta M_1)\Vert _\infty \right) \vert \varphi \vert _{{\mathcal {B}}} + R_1\frac{m(t)}{2}, \end{aligned}$$

here we employ (4.11) and (4.12). Hence, combining with (4.13) one gets

$$\begin{aligned}&\sup _{t\in [0,T_1]}\frac{\Vert {\mathcal {F}}(u)(t)\Vert }{m(t)}\le R_1. \end{aligned}$$

Step 2 (Estimate on the infinite interval \([T_1,\infty )\)). Fixing a number \(R_2\) such that

$$\begin{aligned} \left( \varrho +\Vert r(\cdot ,\lambda _1)*(\beta M_1)\Vert _\infty \right) \vert \varphi \vert _{{\mathcal {B}}} + R_1m(T_1)\Vert r(\cdot ,\lambda _1)*(\beta K_1)\Vert _{BC} \le (1-l_1)R_2. \end{aligned}$$
(4.14)

Then for all \(u\in BC_0({\mathbb {R}}^+; H)\) such that \(\sup _{t\ge T_1}\Vert u(t)\Vert \le R_2\) and for \(t\ge T_1\), we obtain

$$\begin{aligned} \Vert {\mathcal {F}}(u)(t)\Vert&\le s(t,\lambda _1)\Vert \varphi (0)\Vert + \int _0^t r(t-\tau ,\lambda _1)\beta (\tau )\vert u[\varphi ]_\tau \vert _{{\mathcal {B}}}\textrm{d}\tau \\&\le \Vert \varphi (0)\Vert + R_1m(T_1) \int _0^{T_1} r(t-\tau ,\lambda _1)\beta (\tau )K_1(\tau ) \textrm{d}\tau \\&\quad +\int _{T_1}^tr(t-\tau ,\lambda _1)\beta (\tau )K_1(\tau )\left[ \max _{\xi \in [0,T_1]}\Vert u(\xi )\Vert +\max _{T_1\le \xi \le \tau }\Vert u(\xi )\Vert \right] \textrm{d}\tau \\&\quad + \vert \varphi \vert _{{\mathcal {B}}} \int _0^t r(t-\tau ,\lambda _1) \beta (\tau )M_1(\tau )\textrm{d}\tau \\&\le \left( \varrho +\Vert r(\cdot ,\lambda _1)*(\beta M_1)\Vert _\infty \right) \vert \varphi \vert _{{\mathcal {B}}} + R_1m(T_1)\Vert r(\cdot ,\lambda _1)*(\beta K_1)\Vert _{BC}+l_1R_2\\&\le R_2, \end{aligned}$$

thanks to (4.14).

Finally, let consider the set

$$\begin{aligned} {\textbf{D}}=\left\{ u\in {{\mathcal {B}}}{{\mathcal {C}}}_0^\varphi : \sup _{[0,T_1]}\frac{\Vert u(t)\Vert }{m(t)}\le R_1; \sup _{t\ge T_1}\Vert u(t)\Vert \le R_2\right\} . \end{aligned}$$
(4.15)

It is evident that \({\textbf{D}}\) is a closed bounded convex subset of \({{\mathcal {B}}}{{\mathcal {C}}}_0^\varphi \) satisfying \({\mathcal {F}}({\textbf{D}})\subset {\textbf{D}}\). This completes the proof. \(\square \)

Proof of Theorem 4.4

By Lemma 4.7, we have

$$\begin{aligned} {\mathcal {F}} ({\textbf{D}})\subset {\textbf{D}}, \end{aligned}$$

where \({\textbf{D}}\) is given by (4.15). Let \(D^*=\overline{\text {co}}{\mathcal {F}}({\textbf{D}})\), then and \(\pi _T(D^*)\) is compact for all \(T>0\) thanks to Proposition 2.3, and it is also a convex set. In addition, we get \({\mathcal {F}}(D^*)\subset D^*\). Considering \({\mathcal {F}}: D^*\rightarrow D^*\), we show that \({\mathcal {F}}\) is \(\chi ^*\)-condensing. If \(D\subset D^*\), then obviously \(\chi _T(D)=0\), which implies \(\chi _\infty (D)=0\). Using Lemma 4.5, we have

$$\begin{aligned} \chi ^*({\mathcal {F}} (D)) = \chi _\infty ({\mathcal {F}} (D)) + d_\infty ( {\mathcal {F}}(D)) = d_\infty ( {\mathcal {F}} (D))\le \ell \cdot d_\infty (D) \le \ell \cdot \chi ^*(D). \end{aligned}$$

If \(\chi ^*(D)\le \chi ^*({\mathcal {F}}(D))\), then \(\chi ^*(D)\le \ell \cdot \chi ^*(D)\), which yields \(\chi ^*(D)=0\), since \(\ell <1\). This implies that D is relatively compact. Therefore, \({\mathcal {F}}\) is \(\chi ^*\)-condensing. By Theorem 4.3, \({\mathcal {F}}\) possesses a fixed point.

We now show that for all \(u\in {\mathbb {S}}(\varphi )\), \(\vert u_t\vert _{{\mathcal {B}}} \le C\vert \varphi \vert _{{\mathcal {B}}}\) for some \(C>0\).

Let \(t\in [0,T_1]\). The following estimate holds

$$\begin{aligned} \Vert u(t)\Vert&\le s(t,\lambda _1)\Vert \varphi (0)\Vert \\&\quad + \int _0^t r(t-\tau ,\lambda _1)\beta (\tau )\Big (K_1(\tau )\sup _{\xi \in [0,\tau ]}\Vert u(\xi )\Vert +M_1(\tau )\vert \varphi \vert _{{\mathcal {B}}}\Big )\textrm{d}\tau \\&\le s(t,\lambda _1)\varrho \vert \varphi \vert _{{\mathcal {B}}} + \vert \varphi \vert _{{\mathcal {B}}} \int _0^t r(t-\tau ,\lambda _1)\beta (\tau )M_1(\tau )\textrm{d}\tau \\&\quad + \beta _\infty K_{1\infty }\int _0^t r(t-\tau ,\lambda _1)\Big (\sup _{[0,\tau ]}\Vert u(\xi )\Vert \Big )\textrm{d}\tau \\&\le (\varrho +\Vert r(\cdot ,\lambda _1)*(\beta M_1)\Vert _\infty )\vert \varphi \vert _{\mathcal {B}} +\beta _\infty K_{1\infty } \int _0^t r(t-\tau ,\lambda _1)\sup _{[0,\tau ]}\Vert u(\xi )\Vert \textrm{d}\tau . \end{aligned}$$

Since the last integral is nondecreasing with respect to t, one can take the supremum over [0, t] to get

$$\begin{aligned} \sup _{[0,t]}\Vert u(\xi )\Vert&\le (\varrho +\Vert r(\cdot ,\lambda _1)*(\beta M_1)\Vert _\infty )\vert \varphi \vert _{{\mathcal {B}}}\\&\quad + \beta _\infty K_{1\infty } \int _0^t r(t-\tau ,\lambda _1)\sup _{[0,\tau ]}\Vert u(\xi )\Vert \textrm{d}\tau . \end{aligned}$$

The Gronwall type inequality [14, Proposition 2.2] gives

$$\begin{aligned} \sup _{[0,t]}\Vert u(\xi )\Vert \le Y(t)C_1(\varphi ), \forall t\in [0,T_1], \end{aligned}$$

where \(C_1(\varphi )=(\varrho +\Vert r(\cdot ,\lambda _1)*(\beta M_1)\Vert _\infty )\vert \varphi \vert _{{\mathcal {B}}}\) and Y(t) is the unique solution of Volterra equation

$$\begin{aligned} Y(t)=1+\beta _\infty K_{1\infty } \int _0^tr(t-\tau ,\lambda _1)Y(\tau )\textrm{d}\tau . \end{aligned}$$

Particularly,

$$\begin{aligned} \Vert u(t)\Vert \le Y(T_1)C_1(\varphi ), \forall t\in [0,T_1]. \end{aligned}$$
(4.16)

Now estimating for \(t\ge T_1\), we have

$$\begin{aligned} \Vert u(t)\Vert&\le s(t,\lambda _1)\Vert \varphi (0)\Vert + \int _0^t r(t-\tau ,\lambda _1)\beta (\tau )\Big (K_1(\tau )\sup _{\xi \in [0,\tau ]}\Vert u(\xi )\Vert +M_1(\tau )\vert \varphi \vert _{{\mathcal {B}}}\Big )\textrm{d}\tau \\&\le s(t,\lambda _1)\varrho \vert \varphi \vert _{{\mathcal {B}}} + \vert \varphi \vert _{{\mathcal {B}}} \int _0^t r(t-\tau ,\lambda _1)\beta (\tau )M_1(\tau )\textrm{d}\tau \\&\quad + \int _0^t r(t-\tau ,\lambda _1)\beta (\tau ) K_1(\tau )\Big (\sup _{[0,T_1]}\Vert u(\xi )\Vert +\sup _{[T_1,\tau ]}\Vert u(\xi )\Vert \Big )\textrm{d}\tau \\&\le C_1(\varphi )+\Vert r(\cdot ,\lambda _1)*(\beta K_1)\Vert _{BC}Y(T_1)C_1(\varphi ) \\&\quad +\sup _{[T_1,t]}\Vert u(\xi )\Vert \int _0^t r(t-\tau ,\lambda _1)\beta (\tau )K_1(\tau ))\textrm{d}\tau \\&\le C_1(\varphi )[1+Y(T_1)\Vert r(\cdot ,\lambda _1)*(\beta K_1)\Vert _{BC}] + l_1 \sup _{[T_1,t]}\Vert u(\xi )\Vert , \end{aligned}$$

thanks to Lemma 4.7. Let t vary on \([T_1,T]\) for an arbitrary \(T>T_1\), one concludes that

$$\begin{aligned} \sup _{[T_1,T]}\Vert u(t)\Vert \le C_1(\varphi )\left( 1+Y(T_1)\Vert r(\cdot ,\lambda _1)*(\beta K_1)\Vert _{BC}\right) + l_1 \sup _{[T_1,T]}\Vert u(\xi )\Vert . \end{aligned}$$

Consequently,

$$\begin{aligned} \sup _{t\ge T_1}\Vert u(t)\Vert \le \frac{1}{1-l_1}C_1(\varphi )\left( 1+Y(T_1)\Vert r(\cdot ,\lambda _1)*(\beta K_1)\Vert _{BC}\right) . \end{aligned}$$
(4.17)

Combing (4.16) with (4.17), we finally obtain

$$\begin{aligned} \Vert u(t)\Vert \le C_2\vert \varphi \vert _{{\mathcal {B}}}{} {\textbf {}},\forall t>0, \end{aligned}$$

where

$$\begin{aligned} C_2=\frac{\varrho +\Vert r(,\lambda _1)*(\beta M_1)\Vert _\infty }{1-l_1}\left( 1+Y(T_1)\Vert r(\cdot ,\lambda _1)*(\beta K_1)\Vert _{BC}\right) . \end{aligned}$$

This implies

$$\begin{aligned} \vert u_t\vert _{{\mathcal {B}}}&\le M(t)\vert \varphi \vert _{\mathcal B} + K(t)\sup _{[0,t]}\Vert u(\xi )\Vert \le \left[ M(t)+{K(t)}C_2\right] \vert \varphi \vert _{{\mathcal {B}}}\le C|\varphi |_{{\mathcal {B}}}, \end{aligned}$$
(4.18)

where \(C=M_\infty +{K_\infty }C_2\).

We now show that \(\lim \nolimits _{t\rightarrow \infty }\vert u_t\vert _{\mathcal B}=0\). By properties of phase space, we have

$$\begin{aligned} \vert u_t\vert _{{\mathcal {B}}}&\le K(t/2)\sup _{[t/2,t]}\Vert u(\xi )\Vert +M(t/2)\vert u[\varphi ]_{t/2}\vert _{{\mathcal {B}}} \end{aligned}$$
(4.19)
$$\begin{aligned}&\le K_\infty \sup _{[t/2,t]}\Vert u(\xi )\Vert +M(t/2)C\vert \varphi \vert _{{\mathcal {B}}}, \end{aligned}$$
(4.20)

thanks to (4.18).

Because \(\lim \nolimits _{t\rightarrow \infty }\Vert u(t)\Vert =0\) and \(M\in BC_0\), for any \(\epsilon >0\), there exists a positive \(T(\epsilon )>0\) such that

$$\begin{aligned} \Vert u(t)\Vert<\epsilon ,\quad \Vert M(t)\Vert < \epsilon , \text { for all }t>T(\epsilon ). \end{aligned}$$

Combining with the inequality (4.20) gives

$$\begin{aligned} \vert u_t\vert _{{\mathcal {B}}} \le (K_\infty +C|\varphi |_{\mathcal B})\epsilon ,\; \forall t>2T(\epsilon ). \end{aligned}$$

The proof is completed. \(\square \)

Remark 4.1

The statement in Theorem 4.4 presents a new observation, even for bounded delays. In [16, Theorem 7], the weakly asymptotic stability was proved under a condition on the magnitude of coefficients on the half-line. In contrast to the latter, the conditions in Theorem 4.4 involves only the asymptotic information of \(\beta (t)\) near infinity. For example, if \(\beta \in BC({\mathbb {R}}^+)\) such that

$$\begin{aligned} \limsup _{t\rightarrow \infty }\beta (t)<\lambda _1/K_\infty , \end{aligned}$$

then the assumptions in Theorem 4.4 are testified even for \(\beta \) possessing large values in a finite interval.

5 Example

Let \(\Omega \subset {\mathbb {R}}^N\) be a bounded domain which has smooth boundary \(\partial \Omega \). We consider the following multi-term fractional-in-time PDE:

$$\begin{aligned} \sum _{i=1}^m\mu _i\partial _t^{\alpha _i} u(t,x) - \Lambda u(t,x) =&\; b(t, x) \int _{-\infty }^0 \int _{\Omega }\nu (\theta , y)\kappa (y, u(t+\theta , y))\textrm{d}y\textrm{d}\theta , \end{aligned}$$
(5.1)
$$\begin{aligned}&\;\text { for } t>0, x \in \Omega ,\nonumber \\ u(t,x) =&\; 0,\; \text { for } t\ge 0,\; x\in \partial \Omega , \end{aligned}$$
(5.2)
$$\begin{aligned} u(s,x) =&\varphi (s,x), x\in \Omega , s\in (-\infty , 0], \end{aligned}$$
(5.3)

where \(0<\alpha _1<\alpha _2<\cdots<\alpha _m<1\), \(\mu _i> 0\), \(\partial _t^{\alpha _i}\) denote the Caputo fractional derivatives of order \(\alpha _i\) in t, for \(i=\overline{1,m}\). The operator \(\Lambda \) is determined by

$$\begin{aligned} D(\Lambda ) = \{u\in H_0^1(\Omega ): \Lambda u\in L^2(\Omega )\},\;\Lambda u = \sum _{i,j=1}^N\partial _{x_i}(a_{ij}(x)\partial _{x_j} u), \end{aligned}$$

where \(a_{ij}\in L^\infty (\Omega ), a_{ij}=a_{ji}, 1\le i,j\le N\), and fulfills the uniformly elliptic condition \(\sum \nolimits _{i,j=1}^N a_{ij}(x)\xi _i\xi _j\ge \theta |\xi |^2\), for some \(\theta >0\). Applying the Friedrichs theory [25, Prop. 8.5], \(-\Lambda \) is a positive self-adjoint operator with compact resolvent.

Let H be the Hilbertian space \(L^2(\Omega )\) furnished with the standard inner product \(\displaystyle (u,v)=\int _\Omega u(x)v(x)\textrm{d}x\). Set

$$\begin{aligned} k(t)&= \sum \limits _{i=1}^m \mu _i g_{1-\alpha _i}(t),\\ A&= -\Lambda . \end{aligned}$$

Clearly k is completely monotonic, so the associated kernel l exists. Furthermore, the Laplace transform of l is calculated as follows

$$\begin{aligned} {\hat{l}}(\lambda ) = \lambda ^{-1}{\hat{k}}(\lambda )^{-1} = \frac{1}{\mu _i \sum \limits _{i=1}^m \lambda ^{\alpha _i}}. \end{aligned}$$

Thus

$$\begin{aligned} \widehat{(1*l)}(\lambda ) = \frac{1}{\mu _i \sum \limits _{i=1}^m \lambda ^{\alpha _i+1}}\sim \frac{1}{\mu _1\lambda ^{\alpha _1+1}}\text { as } \lambda \rightarrow 0. \end{aligned}$$

Hence \(l\not \in L^1({\mathbb {R}}^+)\) which follows from the asymptotic expansion

$$\begin{aligned} (1*l)(t)\sim \frac{t^{\alpha _1}}{\mu _1\Gamma (\alpha _1+1)} \rightarrow \infty \text { as } t\rightarrow \infty , \end{aligned}$$

thanks to the Karamata–Feller Tauberian theorem (see [6]).

We are now in a position to give the description for the nonlinearity:

  1. (A1)

    \(b\in BC({\mathbb {R}}^+; L^2(\Omega ))\).

  2. (A2)

    \(\nu :(-\infty , 0]\times \Omega \rightarrow {\mathbb {R}}\) is a continuous function and there exist a nonnegative function \(\omega \in L^2(\Omega )\) and \(\nu _0\in (0,1)\) such that

    $$\begin{aligned} |\nu (t, x)|\le \omega (x) e^{\nu _0 t},\text { for all } t \in (-\infty , 0], x\in \Omega . \end{aligned}$$
  3. (A3)

    \(\kappa : \Omega \times {\mathbb {R}}\rightarrow {\mathbb {R}}\) is continuous and there exist a nonnegative function \(p\in L^2(\Omega )\) and \(q\in {\mathbb {R}}^+\) satisfying

    $$\begin{aligned} |\kappa (y, z)|\le p(y) + q |z|. \end{aligned}$$

In this example, we choose the phase space \({\mathcal {B}} = CL^1_g\) with \(r=0\) and \(g(s)=e^{\nu _0 s}\). The seminorm in \({\mathcal {B}}\) is given by

$$\begin{aligned} |w|_{{\mathcal {B}}} = \Vert w(0)\Vert +\int _{-\infty }^{0}e^{\nu _0\theta }\Vert w(\theta )\Vert \textrm{d}\theta . \end{aligned}$$

Then one can see that (2.1)–(2.2) are satisfied with \(G(s)=g(s)\). Then \({\mathcal {B}}\) satisfies (B1)–(B3) with

$$\begin{aligned} K(t)= 1+\nu _0^{-1}(1-e^{-\nu _0t}), \; M(t)= e^{- \nu _0 t}, \end{aligned}$$

thanks to the expressions of K and M in (2.3) and (2.4), respectively. Obviously, \(M\in BC_0\) and \(K_\infty = 1+\nu _0^{-1}.\)

Let \(f: \mathbb {R^+}\times {\mathcal {B}} \rightarrow L^2(\Omega )\) be defined as

$$\begin{aligned}&f(t,\phi )(x) =b(t, x)\int _{-\infty }^0 \int _{\Omega }\nu (\theta , y)\kappa (y, \phi (\theta , y))\textrm{d}y\textrm{d}\theta . \end{aligned}$$

Then the problem (5.1)–(5.3) can be rewritten in the form (1.1)–(1.2).

We now testify the conditions related to f in Theorems 3.3 and 4.4.

For every \(\phi \in {\mathcal {B}}\), we obtain

$$\begin{aligned} \Vert f(t,\phi )\Vert ^2&=\int _{\Omega } \Big | b(t,x)\int _{-\infty }^0 \int _{\Omega }\nu (\theta , y)\kappa (y, \phi (\theta , y))\textrm{d}y\textrm{d}\theta \Big |^2\textrm{d}x \\&\le \Vert b(t,\cdot )\Vert ^2 \Big [ \int _{-\infty }^0 \int _{\Omega }|\nu (\theta , y)|\big (p(y)+q|\phi (\theta , y)|\big )\textrm{d}y\textrm{d}\theta )\Big ]^2 \\&\le \Vert b(t,\cdot )\Vert ^2 \Big [ \int _{-\infty }^0 e^{\nu _0\theta }\int _{\Omega }\big (\omega (y)p(y)+q\omega (y)|\phi (\theta , y)|\big )\textrm{d}y\textrm{d}\theta )\Big ]^2,\\&\le \Vert b(t,\cdot )\Vert ^2 \Big [ \int _{-\infty }^0 e^{\nu _0\theta }\Vert \omega \Vert \big (\Vert p\Vert +q\Vert \phi (\theta ,\cdot )\Vert \big )\textrm{d}\theta \Big ]^2\\&\le \Vert b(t,\cdot )\Vert ^2 \Vert \omega \Vert ^2\Big [ \nu _0^{-1}\Vert p\Vert + q\int _{-\infty }^0 e^{\nu _0\theta } \Vert \phi (\theta ,\cdot )\Vert \textrm{d}\theta \Big ]^2, \end{aligned}$$

thanks to (A2) and (A3) and the Hölder inequality.

Hence

$$\begin{aligned} \Vert f(t,\phi )\Vert \le \Vert b(t,\cdot )\Vert \Vert \omega \Vert \Big [ \nu _0^{-1}\Vert p\Vert + q|\phi |_{{\mathcal {B}}}\Big ]. \end{aligned}$$

By taking

$$\begin{aligned} \alpha (t) = \Vert b(t,\cdot )\Vert \Vert \omega \Vert \nu _0^{-1}\Vert p\Vert ,\;\beta =q \Vert \omega \Vert \sup _{t\ge 0}\Vert b(t,\cdot )\Vert , \end{aligned}$$

we see that \(r(\cdot , \lambda _1)*\alpha \in BC({\mathbb {R}}^+)\) due to (A1).

Applying Theorem 3.3, if \(\beta \big (1+\nu _0^{-1} \big )<\lambda _1 \) then our system is dissipative.

On the other hand, let \(p=0\) then (4.6) takes place with

$$\begin{aligned} \beta (t)= q\Vert \omega \Vert \Vert b(t,\cdot )\Vert . \end{aligned}$$

Let \({\tilde{\beta }}=\limsup \limits _{t\rightarrow \infty }\beta (t)\). Then the condition

$$\begin{aligned} {\tilde{\beta }} \big (1+\nu _0^{-1} \big )<\lambda _1 \end{aligned}$$
(5.4)

implies (4.7). By Theorem 4.4, the zero solution of (1.1) is weakly asymptotically stable if the last inequality (5.4) holds. Note that condition (5.4) holds even for \(\sup _{t\ge 0}\beta (t)\) being large.

We now replace (A3) with the following one

  1. (A3b)

    \(\kappa : \Omega \times {\mathbb {R}}\rightarrow {\mathbb {R}}\) is a continuous function and there exists \(q>0\) such that

    $$\begin{aligned} |\kappa (y, z_1)-\kappa (y, z_2)|\le q|z_1-z_2|. \end{aligned}$$

Then, we have the following estimates

$$\begin{aligned}&\Vert f(t,\phi _1)-f(t,\phi _2)\Vert ^2\\&\quad =\int _{\Omega } \Big | b(t,x)\int _{-\infty }^0 \int _{\Omega }\nu (\theta , y)\big (\kappa (y, \phi _1(\theta , y))-\kappa (y, \phi _1(\theta _2, y))\big )\textrm{d}y\textrm{d}\theta \Big |^2\textrm{d}x \\&\quad \le \Vert b(t,\cdot )\Vert ^2 q^2\Big [ \int _{-\infty }^0 \int _{\Omega }|\nu (\theta , y)||\phi _1(\theta , y)-\phi _2(\theta , y)|\textrm{d}y\textrm{d}\theta )\Big ]^2 \\&\quad \le \Vert b(t,\cdot )\Vert ^2 q^2\Big [ \int _{-\infty }^0 e^{\nu _0\theta }\int _{\Omega }\omega (y)|\phi _1(\theta , y)-\phi _2(\theta , y)|\textrm{d}y\textrm{d}\theta )\Big ]^2\\&\quad \le \Vert b(t,\cdot )\Vert ^2 q^2\Big [ \int _{-\infty }^0 e^{\nu _0\theta }\Vert \omega \Vert \Vert \phi _1(\theta , \cdot )-\phi _2(\theta , \cdot )\Vert \textrm{d}\theta )\Big ]^2\\&\quad \le q^2\Vert b(t,\cdot )\Vert ^2 \Vert \omega \Vert ^2 |\phi _1-\phi _2|_{\mathcal B}^2. \end{aligned}$$

It leads to

$$\begin{aligned} \Vert f(t,\phi _1)-f(t,\phi _2)\Vert \le q\Vert \omega \Vert \Vert b(t,\cdot )\Vert |\phi _1-\phi _2|_{{\mathcal {B}}}, \end{aligned}$$

that is, f satisfies the Lipschitz condition with Lipschitz constant

$$\begin{aligned} \beta =q\Vert \omega \Vert \sup _{t\ge 0}\Vert b(t,\cdot )\Vert . \end{aligned}$$

Employing Theorem 4.1, one concludes that the solution to (5.1)–(5.3) is asymptotically stable provided that \(\beta (1+\nu _0^{-1})<\lambda _1\).

6 Conclusion

In this paper, we establish stability results for a class of nonlocal evolution equations in Hilbert spaces involving infinite delays. The techniques are based on local estimates, fixed-point arguments, the resolvent theory of Prüss and the phase space axioms. By relaxing some sufficient conditions, the obtained results have improved and extended the previous works in the literature.