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. 2021 Nov 18;23(11):1535. doi: 10.3390/e23111535

Modulo Periodic Poisson Stable Solutions of Quasilinear Differential Equations

Marat Akhmet 1,*, Madina Tleubergenova 2, Akylbek Zhamanshin 1,2
Editor: Jiri Petrzela
PMCID: PMC8625164  PMID: 34828232

Abstract

In this paper, modulo periodic Poisson stable functions have been newly introduced. Quasilinear differential equations with modulo periodic Poisson stable coefficients are under investigation. The existence and uniqueness of asymptotically stable modulo periodic Poisson stable solutions have been proved. Numerical simulations, which illustrate the theoretical results are provided.

Keywords: modulo periodic Poisson stable functions, quasilinear differential equations, modulo periodic Poisson stable solutions, asymptotic stability

1. Introduction

The theory of differential equations is a doctrine on oscillations and recurrence, which are basic in science and technique. Oscillations are most preferable in engineering [1], while recurrence originates in celestial mechanics [2]. The ultimate recurrence is the Poisson stability [3,4,5]. Presently, needs for functions with irregular behavior are exceptionally strong in neuroscience and celestial dynamics, which is still in the developing mode. In the present research, we have decided to combine periodic dynamics with the phenomenon of Poisson stability. That is, one of simplest forms of oscillations is amalgamated with the most sophisticated type of recurrence. We hope that the choice can give a new push for the nonlinear analysis, which faces challenging problems of the real world and industry. The present product of the design are modulo periodic Poisson stable functions.

In paper [6], to strengthen the role of recurrence as a chaotic ingredient we have extended the Poisson stability to the unpredictability property. Thus, the Poincaré chaos has been determined, and one can say that the unpredictability implies chaos now. The unpredictable point of the Bebutov dynamics is the unpredictable function. In papers [7,8,9,10,11,12,13,14,15], we provided a dynamical method, how to construct Poisson stable functions. Deterministic and stochastic dynamics have been used. Deterministically unpredictable functions have been constructed as solutions of hybrid systems, consisting of discrete and differential equations [9,13,14], and randomly they are results of the Bernoulli process inserted into a linear differential equation [7,10,16]. Unpredictable oscillations in neural networks have been researched in [7,13,17,18,19].

In papers [8,9,10,14] and books [7,13], discussing existence of unpredictable solutions, we have developed a new method how to approve Poisson stable solutions, since unpredictable functions are a subset of Poisson stable functions, and to verify the unpredictability one must check, if the Poisson stability is valid. The method is distinctly different than the comparability method by character of recurrence, which was introduced in [20] and later has been realized in several articles [21,22,23,24,25,26,27]. Unlike papers [7,8,9,10,13,14,15,16,17,18,19], the present research is busy with the new type of Poisson stable functions. Correspondingly, it is the first time in literature, when quasilinear equations with Poisson stable coefficients are under investigation. Finally, the systems are approved with modulo periodic Poisson stable solutions. The newly invented method of verification of the Poisson stability joined with the presence of the periodic components in the recurrence has made possible the extension for the class of studied differential equations. In papers [21,22,23,24], quasilinear systems are with constant matrices of coefficients, and in our case, we research systems with periodic and, even with Poisson stable coefficients. Another significant novelty is the numerical simulation of the Poisson stable functions and solutions [7,9,13,14]. We believe that altogether, the present suggestions can shape a new interesting science direction, not only in the theoretical study of differential equations, but also they provide rich opportunities for applications in mechanics, electronics, artificial neural networks, neuroscience.

2. Preliminaries

Throughout the paper, R and N will stand for the set of real and natural numbers, respectively. Additionally, the norm u1=suptRu(t), where u=max1inui, u=(u1,,un),uiR,i=1,2,...,n, will be used. Correspondingly, for a square matrix A={aij},i,j=1,2,...,n, the norm A=maxi=1,,nj=1n|aij| will be used.

Definition 1

([5]). A continuous and bounded function ψ(t):RRn is called Poisson stable, if there exists a sequence tk, which diverges to infinity such that the sequence ψ(t+tk) converges to ψ(t) uniformly on bounded intervals of R.

The sequence tk in the last definition is said to be Poisson sequence of the function ψ(t).

By Lemma A1 in the Appendix A, for a positive fixed ω there exist a subsequence tkl of the Poisson sequence tk and a number τω such that tklτω(modω) as l. We shall call the number τω as the Poisson shift for the Poisson sequence tk with respect to the ω. It is not difficult to find that for the fixed ω the set of all Poisson shifts, Tω, is not empty, and it can consist of several and even infinite number elements. The number κω=infTω, 0κω<ω, is said to be the Poisson number for the Poisson sequence tk with respect to the number ω.

Definition 2.

The sum ϕ(t)+ψ(t) is said to be a modulo periodic Poisson stable (MPPS) function, if ϕ(t) is a continuous periodic and ψ(t) is a Poisson stable functions.

We shall call the function ϕ(t) the periodic component and the function ψ(t) the Poisson component of the MPPS function in what follows.

Remark 1.

Duo to Lemma A3, an MPPS function is a Poisson stable if κω equals zero. Otherwise, without loss of generality, the sequence ϕ(t+tk)+ψ(t+tk) converges on all compact subsets of the real axis to the function ϕ(t+τω)+ψ(t), where τω is a nonzero Poisson shift for the sequence tk. Since of the periodicity of the function ϕ(t), one can accept the last convergence as a special form of recurrence. In the next section, we shall consider it as a result of Theorem 1.

3. Main Results

3.1. Linear System of Differential Equations

Consider the following system

x(t)=A(t)x(t)+ϕ(t)+ψ(t), (1)

where tR, xRn, nN, ϕ(t):RRn and ψ(t):RRn are continuous functions, A(t) is a continuous n×n matrix.

We assume that the following conditions are satisfied.

  • (C1) 

    A(t) is an ω periodic matrix for a fixed positive ω;

  • (C2) 

    ϕ(t) is an ω periodic function, and ψ(t) is a Poisson stable function with a Poisson sequence tk;

  • (C3) 

    the Poisson number κω for the sequence tk is equal to zero.

According to Definition 2 and condition (C2), the sum ϕ(t)+ψ(t) is an MPPS function, i.e., the linear system (1) is with MPPS perturbation.

Let us consider the homogeneous system, associated with (1),

x(t)=A(t)x(t). (2)

Let X(t), tR, is the fundamental matrix of the system (2) such that X(0)=I, and I is the n×n identical matrix. Moreover, X(t,s) is transition matrix of the system (2), which equal to X(t)X1(s), and X(t+ω,s+ω)=X(t,s) for all t,sR.

We assume that the following additional assumption is valid.

  • (C4) 

    The multipliers of the system (2) in modulus are less than one.

It follows from the last condition that there exist positive numbers K1 and α such that

X(t,s)Keα(ts), (3)

for ts [28].

Lemma 1.

If the inequality (3) is satisfied, then the following estimation is correct

X(t+τ,s+τ)X(t,s)maxtRA(t+τ)A(t)2K2α2eeα2(ts), (4)

for ts and arbitrary real number τ.

Proof. 

Since

dX(t+τ,s+τ)dt=A(t)X(t+τ,s+τ)+(A(t+τ)A(t))X(t+τ,s+τ),

we have that

X(t+τ,s+τ)=X(t,s)+stX(t,u)(A(u+τ)A(u))X(u+τ,s+τ)du.

That is why,

X(t+τ,s+τ)X(t,s)stX(t,u)A(u+τ)A(u)X(u+τ,s+τ)dumaxtRA(t+τ)A(t)stK2eα(ts)du=maxtRA(t+τ)A(t)K2αeα(ts)(ts)=maxtRA(t+τ)A(t)K2αeα2(ts)eα2(ts)(ts).

Since supu0eα2uu=2αe, the lemma is proved.  □

Theorem 1.

Assume that conditions (C1), (C2) and (C4) are valid. Then the system (1) admits a unique asymptotically stable MPPS solution.

Proof. 

The bounded solution of system (1) has the form [28]

x(t)=tX(t,s)[ϕ(s)+ψ(s)]ds,tR. (5)

One can write that x(t)=xϕ(t)+xψ(t), where xϕ(t)=tX(t,s)ϕ(s)ds and xψ(t)=tX(t,s)ψ(s)ds.

It is not difficult to show that the function xϕ(t) is ω periodic [29].

Next, we prove that the function xψ(t) is Poisson stable. Fix arbitrary positive number ϵ and interval [a,b], <a<b<. We will show that for a large k it is true that xψ(t+tk)xψ(t)<ϵ on [a,b]. Let us choose two numbers c and ξ such that c<a and ξ is positive, satisfying the following inequalities,

4K2mψα3eξ<ϵ3, (6)
2Kmψαeα(ac)<ϵ3, (7)

and

Kξα[1eα(bc)]<ϵ3, (8)

with mψ=suptRψ(t). By applying condition (C4), without loss of generality, for sufficiently large k we obtain that A(t+tk)A(t)<ξ for all tR, and ψ(t+tk)ψ(t)<ξ for t[c,b]. Using Lemma 1 we attain that

xψ(t+tk)xψ(t) = tX(t+tk,s+tk)ψ(s+tk)X(t,s)ψ(s)dstX(t+tk,s+tk)X(t,s)ψ(s+tk)ds +tX(t,s)ψ(s+tk)ψ(s)ds=tX(t+tk,s+tk)X(t,s)ψ(s+tk)ds +cX(t,s)ψ(s+tk)ψ(s)ds +ctX(t,s)ψ(s+tk)ψ(s)dst2K2ξα2eeα2(ts)mψds+t2Keα(ts)mψds+tKeα(ts)ξds4K2ξα3emψ+2Kmψαeα(ac)+Kξα[1eα(bc)].

Now, the inequalities (6) to (8) imply that xψ(t+tk)xψ(t)<ϵ, for t[a,b]. Therefore, the sequence xψ(t+tk) uniformly converges to xψ(t) on each bounded interval. Thus, according to the Definition 2 the solution x(t) of the system (1) is MPPS function with the periodic component xϕ(t) and the Poisson component xψ(t). The asymptotic stability of the MPPS solution can be verified in the same way as for the bounded solution of a linear inhomogeneous system [29].  □

The following examples show the validity of the obtained theoretical result.

Example 1.

Let us consider the following linear inhomogeneous system,

x1=(1+0.5sin(2t))x1+2.5cos(t)+5.5Θ2(t),x2=(2+0.25cos(t))x2+2sin(2t)+1.7Θ(t), (9)

where Θ(t)=te3(ts)Ω(3.85;6π)(s)ds is the Poisson stable function described in Appendix B. The perturbation is an MPPS function with the periodic component ϕ(t)=2.5cos(t),2sin(2t)T and the Poisson component ψ(t)=5.5Θ2(t),1.7Θ(t)T. The common period of the coefficient A(t) and the periodic component ϕ(t) is 2π. Since the function Ω(3.85,6π)(t) is constructed on the intervals [6πi,6π(i+1)), iZ, for the Poisson sequence tk of the function Θ(t) there exists a subsequence tkl such that tkl0(mod2π). Therefore, the Poisson number κω=0. Condition (C4) is valid with the multipliers ρ1=e2π, and ρ2=e4π. According to Theorem 1, the system admits a unique asymptotically stable MPPS solution, z(t). Since it is impossible to determine the initial value of the solution, we simulate a solution, which asymptotically approaches z(t) as time increases. We depict in Figure 1 the coordinates of the solution x(t), with initial values x1(0)=2.5 and x2(0)=1.5, which visualizes the MPPS solution approximately. In Figure 2 the trajectory of the solution x(t) is shown.

Figure 1.

Figure 1

Coordinates of the solution x(t) of system (9) with initial values x1(0)=2.5 and x2(0)=1.5, which asymptotically converge to the coordinates of the MPPS solution z(t) of the system.

Figure 2.

Figure 2

The trajectory of the solution x(t) of the Equation (9), which asymptotically approaches the MPPS solution z(t) of the system.

In the next example, the periodic component ϕ(t) of the MPPS perturbation is absent, but the condition (C2) is correct, since a constant function is of arbitrary period. It is remarkable to say that the absence of a proper non-constant periodic component makes the dynamics more irregular, this is seen in Figure 3 and Figure 4.

Figure 3.

Figure 3

Coordinates of the solution x(t), with initial values x1(0)=1, x2(0)=1 and x3(0)=1, which asymptotically converge to the coordinates of the MPPS solution of system (10).

Figure 4.

Figure 4

The trajectory of the solution, x(t), of Equation (10), which asymptotically approaches the MPPS solution of the equation.

Example 2.

Consider the inhomogeneous linear system

x1=(0.25+0.5cos(πt))x1+12Θ3(t),x2=(1.5+sin2(πt))x2+8Θ2(t),x3=(0.5+cos(2π3t))x3+6Θ(t), (10)

where Θ(t)=te2(ts)Ω(3.9;6)(s)ds. The conditions (C1)–(C3) are satisfied, and condition (C4) is valid with multipliers ρ1=e0.75, ρ2=e3 and ρ3=e1.5. Consequently, there exists the unique asymptotically stable MPPS solution of the system (10). Figure 3 presents the coordinates of the solution x(t) with initial values x1(0)=1, x2(0)=1 and x3(0)=1. The coordinates of solution x(t) approximate the coordinates of the MPPS solution. The trajectory of the solution x(t) is shown in Figure 4.

3.2. Quasilinear Differential Equations

The main object of the present section is the system of quasilinear differential equations

x(t)=A(t)x+g(t,x)+ϕ(t)+ψ(t), (11)

where tR,xRn,n is a fixed natural number; A(t) is n dimensional square matrix and satisfies to the condition (C1) and inequality (3); g:R×URn,g=(g1,,gn), U={xRn,x<H}, where H is a fixed positive number; the functions ϕ(t) and ψ(t) satisfy conditions (C2) and (C3).

The following conditions on system (11) are required.

  • (C5) 

    the function g(t,x) is continuous and ω periodic in t;

  • (C6) 

    there exists a positive constant L such that g(t,x1)g(t,x2)Lx1x2 for all tR,x1,x2U.

We denote supR×Ug(t,x)=mg, maxtRϕ(t)=mϕ and suptRψ(t)=mψ.

The following additional conditions will be needed:

  • (C7) 

    K(mg+mϕ+mψ)H<α;

  • (C8) 

    KL<α.

For simplicity, we use the notation F(t,x)=g(t,x)+ϕ(t)+ψ(t) in what follows.

According to [28], a bounded on the real axis function y(t) is a solution of (11), if and only if it satisfies the equation

y(t)=tX(t,s)F(s,y(s))ds,tR. (12)

Theorem 2.

If conditions (C1)–(C8) are valid, then the system (11) possesses a unique asymptotically stable Poisson stable solution.

Proof. 

Let tk is the Poisson sequence of the function ψ(t) in the system (11). We denote by B the set of all Poisson stable functions ν(t)=(ν1,ν2,...,νn), νiR, i=1,2,...,n, with common Poisson sequence tk, which satisfy ν1<H.

Let us show that the B is a complete space. Consider a Cauchy sequence θm(t) in B, which converges to a limit function θ(t) on R. We have that

θ(t+tk)θ(t)<θ(t+tk)θm(t+tk)+θm(t+tk)θm(t)+θm(t)θ(t). (13)

for a fixed closed and bounded interval IR. Now, one can take sufficiently large m and k such that each term on the right hand-side of (13) is smaller than ϵ3 for a fixed positive ϵ and tI, i.e., the sequence θ(t+tk) uniformly converges to θ(t) on I. Likewise, one can check that the limit function is uniformly continuous [28]. The completeness of B is shown.

Define the operator Π on B such that

Πν(t)=tX(t,s)F(s,ν(s))ds,tR. (14)

Fix a function ν(t) that belongs to B. We have that

Πν(t)tX(t,s)F(s,ν(s))dsK(mg+mϕ+mψ)α

for all tR. Therefore, by the condition (C7) it is true that Πν1<H.

Fix a positive number ϵ and an interval [a,b], <a<b<. Let us choose two numbers c<a, and ξ>0 satisfying the inequalities

4K2ξα3e(mg+mϕ+mψ)<ϵ3, (15)
2Kα(mg+mϕ+mψ)eα(ac)<ϵ3, (16)

and

Kξα[1eα(bc)]<ϵ3. (17)

Using the condition (C4) and Lemmas A3 and A5 from Appendix A, without loss of generality, we obtain that A(t+tk)A(t)<ξ for all tR, and F(t+tk,ν(t+tk))F(t,ν(t))<ξ for t[c,b] and sufficiently large k. Then, applying the inequality (4), we obtain:

Πν(t+tk)Πν(t)=tX(t+tk,s+tk)F(s+tk,ν(s+tk))dstX(t,s)F(s,ν(s))dstX(t+tk,s+tk)X(t,s)F(s+tk,ν(s+tk))ds+cX(t,s)F(s+tk,ν(s+tk))F(t,s)ds+ctX(t,s)F(s+tk,ν(s+tk))F(t,s)dst2K2ξα2eeα2(ts)(mg+mϕ+mψ)ds+t2Keα(ts)(mg+mϕ+mψ)ds+tKeα(ts)ξds4Kξα3e(mg+mϕ+mψ)+2Kα(mg+mϕ+mψ)eα(ac)+Kξα[1eα(bc)],

for all t[a,b]. From inequalities (15)–(17) it follows that Πν(t+tk)Πν(t)<ϵ for t[a,b]. Therefore, Πν(t+tk) uniformly converges to Πν(t) on bounded interval of R.

It is easy to verify that Πν(t) is a uniformly continuous function, since its derivative is a uniformly bounded function on the real axis. Summarizing the above discussion, the set B is invariant for the operator Π.

We proceed to show that the operator Π:BB is contractive. Let u(t) and v(t) be members of B. Then, we obtain that

Πu(t)Πv(t)tX(t,s)F(s,u(s))F(s,v(s))dstKeα(ts)Lu(s)v(s)dsKLαu(t)v(t)1,

for all tR. Therefore, the inequality ΠuΠv1KLαuv1 holds, and according to the condition (C8) the operator Π:BB is contractive.

By the contraction mapping theorem there exists the unique fixed point, x¯(t)B, of the operator Π, which is the unique bounded Poisson stable solution of the system (11).

Finally, we will study the asymptotic stability of the Poisson stable solution x¯(t) of the system (11). It is true that

x¯(t)=X(t,t0)x¯(t0)+t0tX(t,s)g(s,x¯(s))+ϕ(s)+ψ(s)ds,

for tt0.

Let x(t) be another solution of system (11). One can write

x(t)=X(t,t0)x(t0)+t0tX(t,s)g(s,x(s))+ϕ(s)+ψ(s)ds.

Making use of the relation

x¯(t)x(t)=X(t,t0)(x¯(t0)x(t0))+t0tX(t,s)g(s,x¯(s))g(s,x(s))ds,

we obtain that

x¯(t)x(t)X(t,t0)x¯(t0)x(t0)+t0tX(t,s)g(s,x¯(s))g(s,x(s)dsKeα(tt0)x¯(t0)x(t0)+t0tKLeα(ts)x¯(s)x(s)ds.

Now, applying Gronwall–Bellman Lemma, one can attain that

x¯(t)x(t)Ke(αKL)(tt0)x¯(t0)x(t0),tt0. (18)

The last inequality and condition (C8) confirm that the Poisson stable solution x¯(t) is asymptotically stable. The theorem is proved.  □

Remark 2.

According to the Lemma A4 in the Appendix A, the Poisson stable solution x¯(t) of the system (11) is an MPPS function.

Example 3.

Consider the quasilinear system.

x1=(1.5+2sin(2t))x1+0.01cos(2t)arctg(x2)+1.2sin(8t)10.5Θ3(t),x2=(3.5+3sin2(2t))x2+0.03sin(4t)arctg(x3)1.5cos(8t)+2.5Θ(t),x3=(1.5+2cos2(t))x30.02sin(2t)arctg(x1)+sin(4t)+7.2Θ2(t), (19)

where Θ(t)=te3(ts)Ω(3.86,3π)(s)ds is the Poisson stable function, which described similarly to that in Appendix B. Since, the piecewise constant function Ω(3.86;3π)(t) is given on intervals [3πi,3π(i+1)), for the Poisson sequence tk of the function Θ(t) there exists a subsequence tkl such that tkl0(modπ), that is the condition (C3) is valid. The common period of the matrix A(t) and functions g(t,x), ϕ(t) is equal to π. We have that the function g(t,x)=(0.01cos(2t)arctg(x2),0.03sin(4t)arctg(x3),0.02sin(2t)arctg(x1))T is continuous and π periodic in t and satisfies condition (C6) with L=0.03. The sum of ϕ(t)=(1.2sin(8t),1.5cos(8t),sin(4t))T and ψ(t)=(10.5Θ3(t),2.5Θ(t),7.2Θ2(t))T is an MPPS function, which meets conditions (C2), (C3). The assumptions (C4)–(C8) are valid with mg=0.048, mϕ=1.5, mψ=0.84, ρ1=e1.5π, ρ2=e2π, ρ3=e0.5π, α=0.5π, K=1, and H=4.8. Thus, all conditions for the last theorem have been verified, and there is the Poisson stable solution of the system, which is asymptotically stable.

It is worth noting that the simulation of the Poisson stable solution, x¯(t), is not possible, since the initial value is not known precisely. For this reason, we will consider the solution x(t) of the system (19), with initial values x1(0)=1, x2(0)=1 and x3(0)=1. Using the inequality (18) one can obtain that x¯(t)x(t)e1.54x¯(0)x(0) for t0. The last inequality shows that x¯(t)x(t) decreases exponentially. Consequently, the graph of the solution x(t) asymptotically approaches the Poisson stable solution x¯(t) of the system (19), as time increases. The Figure 5 demonstrates the coordinates of the solution x(t), which illustrate the Poisson stability of the system (19). In the Figure 6 the trajectory of the function x(t) is depicted.

Figure 5.

Figure 5

The coordinates of the solution x(t), with x1(0)=1, x2(0)=1, x3(0)=1, which is asymptotic for the Poisson stable solution of the system (19).

Figure 6.

Figure 6

The trajectory of the solution x(t), with x1(0)=1, x2(0)=1, x3(0)=1, which illustrates the Poisson stability of the system (19).

3.3. A Case with MPPS Coefficients

Let us consider the quasilinear Equation (11) with A(t)=B(t)+D(t), where B(t) is a continuous ω periodic matrix, and D(t) is a Poisson stable matrix with the Poisson sequence tk. That is, the coefficient is an MPPS matrix and the system (11) is of the form

x(t)=(B(t)+D(t))x+g(t,x)+ϕ(t)+ψ(t), (20)

where the functions ϕ(t) and ψ(t) satisfy conditions (C2) and (C3) and their sum is an MPPS function. The function g(t,x) satisfies conditions (C5), (C6).

Denote G(t,x)=D(t)x+g(t,x)+ϕ(t)+ψ(t) and rewrite the system (20) as

x(t)=B(t)x+G(t,x). (21)

The homogeneous ω periodic system, associated with (20),

y(t)=B(t)y, (22)

has the fundamental matrix Y(t), Y(0)=I, and the transition matrix Y(t,s), t,sR.

Assume that the following assumptions are valid.

  • (C9) 

    The multipliers of the system (22) are in modulus less than one.

From the condition (C9) we have that there exist positive numbers D1 and β such that

Y(t,s)Deβ(ts), (23)

for ts.

  • (C10) 

    D(L+d)<β;

  • (C11) 

    D(mg+mϕ+mψ)H<βDd,

where d=suptRD(t).

Theorem 3.

If conditions (C2), (C3), (C5), (C6), and (C9) to (C11) are hold, then system (20) admits a unique asymptotically stable Poisson stable solution.

Proof. 

A bounded on the real axis function z(t) is a solution of (21), if and only if it satisfies the equation

z(t)=tY(t,s)G(s,z(s))ds,tR. (24)

Denote by U the Banach space of all Poisson stable functions ν(t)=(ν1,ν2,...,νn), νiR, i=1,2,...,n, with common Poisson sequence tk. The functions of space U satisfies the condition ν1<H.

Introduce the operator Γ on U such that

Γν(t)=tY(t,s)G(s,ν(s))ds,tR. (25)

Let us show that the space U is invariant for the operator Γ. Fix a function ν(t) from U. We have that

Γν(t)tY(t,s)G(s,ν(s))dsD(dH+mg+mϕ+mψ)β

for all tR. Condition (C11) implies that Γν1<H.

Next, we will use fixed positive number ϵ and an interval [a,b], <a<b<, and two numbers c<a, and ξ>0 satisfying the following inequalities

4DK2ξβ3e(dH+mg+mϕ+mψ)<ϵ3, (26)
2Dβ(dH+mg+mϕ+mψ)eα(ac)<ϵ3, (27)

and

Dξβ[1eα(bc)]<ϵ3. (28)

Using the condition (C9) and Lemmas A3, A5 from Appendix A, we obtain that B(t+tk)B(t)<ξ for all tR, and G(t+tk,ν(t+tk))G(t,ν(t))<ξ for t[c,b] and sufficiently large k. Then, applying the inequality (4), we obtain

Γν(t+tk)Γν(t)=tY(t+tk,s+tk)G(s+tk,ν(s+tk))dstY(t,s)G(s,ν(s))dstY(t+tk,s+tk)Y(t,s)G(s+tk,ν(s+tk))ds+cY(t,s)G(s+tk,ν(s+tk))G(t,s)ds+ctY(t,s)G(s+tk,ν(s+tk))G(t,s)dst2D2ξβ2eeβ2(ts)(dH+mg+mϕ+mψ)ds+t2Deβ(ts)(dH+mg+mϕ+mψ)ds+tDeβ(ts)ξds4Dξβ3e(dH+mg+mϕ+mψ)+2Dβ(dH+mg+mϕ+mψ)eβ(ac)+Dξβ[1eβ(bc)],

for all t[a,b]. Hence, the inequalities (26)–(28) give that Γν(t+tk)Γν(t)<ϵ for t[a,b]. Therefore, the sequence Γν(t+tk) uniformly converges to Γν(t) on the bounded interval of R. Thus, we have shown that the operator Γ is invariant in U.

Let us show that the operator Γ:UU is contractive. Fix members u(t) and v(t) of U. It is true that

Γu(t)Γv(t)tY(t,s)G(s,u(s))G(s,v(s))dstDeβ(ts)(d+L)u(s)v(s)dsD(d+L)βu(t)v(t)1,

for all tR, and condition (C10) implies that the operator Γ is contractive.

Using the contraction mapping theorem, one can conclude that there exists a unique fixed point, x¯(t), of the operator Γ, which is the Poisson stable solution of the system (20). Let us investigate its stability.

If x(t) is a solution of the Equation (20), then

x¯(t)x(t)=Y(t,t0)(x¯(t0)x(t0))+t0tY(t,s)D(s)(x¯(s)x(s))+(g(s,x¯(s))g(s,x(s))ds,

and

x¯(t)x(t)Y(t,t0)x¯(t0)x(t0)+t0tY(t,s)D(s)(x¯(s)x(s))+g(s,x¯(s))g(s,x(s)dsDeβ(tt0)x¯(t0)x(t0)+t0tD(d+L)eα(ts)x¯(s)x(s)ds.

With the aid of the Gronwall–Bellman Lemma, one can verify that

x¯(t)x(t)De(βD(d+L))(tt0)x¯(t0)x(t0),tt0. (29)

Now, based on the condition (C10), we conclude that the Poisson stable solution x¯(t) of system (20) is asymptotically stable. The theorem is proved.  □

4. Conclusions

In this paper, we have introduced a new type of recurrence, which is the sum of two compartments, periodic and Poisson stable functions. We call it as modulo periodic Poisson stable function. Sufficient conditions for the dynamics to be Poisson stable have been determined. The novelty is convenient for theoretical analysis of differential and discrete equations of various types. In the present paper, we study quasilinear ordinary differential equations. If one consider the periodic compartment in the Poisson stability, and achievements of the paper for simulations of the recurrence, the results create new productive opportunities in the research of mechanical, electronic dynamics and neuroscience. Concerning theoretical research, it is of strong interest to search for Poisson stability and its periodic components in such famous dynamics as Lorenz, Rössler and Chua attractors. Generally speaking, one can look for periodic components of any chaotic dynamics. The results can be applied in problems of optimization. The results can be applied for problems of optimization.

Acknowledgments

M. Akhmet and A. Zhamanshin have been supported by 2247-A National Leading Researchers Program of TUBITAK, Turkey, N 120C138. M. Tleubergenova and A. Zhamanshin have been supported by the Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan (grant No. AP09258737 and No. AP08856170).

Appendix A

Lemma A1.

For arbitrary sequence of positive real numbers tk, k=1,2,, and a positive number ω there exist a subsequence tkl, l=1,2,, and a number τω, 0τω<ω, such that tklτω(modω) as l.

Proof. 

Consider the sequence τk such that tkτk(modω), and 0τk<ω for all k1. The boundedness of the sequence τk implies that there exists a subsequence τkl, which converges to a number τω [30].  □

Lemma A2.

κωTω.

Proof. 

Assume on the contrary that κω is not in Tω. Then there exists a strictly decreasing sequence τm, m1, in Tω, such that τmκω. For each natural m, denote by tim a subsequence of tk such that timτm(modω) as i.

Fix a sequence of positive numbers ϵn, which converges to the zero. One can find numbers in, n=1,2,, such that |tinnτn|<ϵn(modω). It is clear that tinnκω(modω) as n.  □

Remark A1.

The last assertion implies that if κω=0, then there exists a subsequence tkl such that tkl0(modω) as l.

Lemma A3.

If f(t)=ϕ(t)+ψ(t) is an MPPS function, and κω=0, then the function f(t) is Poisson stable.

Proof. 

According to Lemma A2, there exists a subsequence tkl, which tends to zero in modulus ω as l. Without loss of generality assume that tk0(modω) as k. Fix a positive number ϵ, and bounded interval IR. The periodic function ϕ(t) is uniformly continuous on R. Consequently, there exists a number k1 such that

ϕ(t+tk)ϕ(t)<ϵ2,

for all tR and k>k1. Moreover, there exists an integer k2, such that

ψ(t+tk)ψ(t)<ϵ2,

for tI, k>k2. This is why,

f(t+tk)f(t)ϕ(t+tk)ϕ(t)+ψ(t+tk)ψ(t)<ϵ,

if tI and k>max(k1,k2). That is, the function f(t) is Poisson stable.  □

Lemma A4.

Assume that ψ(t) is a Poisson stable function. If κω=0, for some positive number ω, then ψ(t) is MPPS function.

Proof. 

Let us write ψ(t)=g(t)+(ψ(t)g(t)), where g(t) is a continuous ω periodic function. Since κω=0, then the subtraction ψ(t)g(t) is Poisson stable by Lemma A3.  □

Remark A2.

The last result is a source for the optimization problem how to choose the function g(t) and the period ω to minimize the difference ψ(t)g(t). In other words, the problem of approximation of Poisson stable functions with periodic ones. It is of exceptional interest for celestial mechanics [2].

Lemma A5.

Assume that a function G(t,u):R×URn,URn, is a Poisson stable function in t and satisfies the inequality G(t,u1)G(t,u2)Lu1u2, where L is a positive constant, for all tR,u1,u2U. Moreover, υ(t):RU is ω periodic in t. If the Poisson sequence and period ω are such that the Poisson number κω equals to the zero, then the function G(t,υ(t)) is Poisson stable.

Proof. 

By the Lemma A2 there exists a subsequence tkl, such that tkl0(modω) as l. We assume, without loss of generality, that the sequence tk itself satisfies the condition tk0(modω) as k.

Let us fix a positive number ϵ, and a bounded interval I. Since of the property of the sequence tk, we have that for sufficiently large k, it is true that G(t+tk,υ(t+tk))G(t,υ(t+tk))<ϵ2 for all tR, and υ(t+tk)υ(t)<ϵ2L for tI, and

G(t+tk,υ(t+tk))G(t,υ(t))G(t+tk,υ(t+tk))G(t,υ(t+tk))+G(t,υ(t+tk))G(t,υ(t))G(t+tk,υ(t+tk))G(t,υ(t+tk))+Lυ(t+tk)υ(t)ϵ2+Lϵ2Lϵ,

for all tI. That is, G(t,υ(t)) is Poisson stable function.  □

Lemma A6.

Assume that a function G(t,u):R×URn,URn, is ω periodic in t and satisfies the inequality G(t,u1)G(t,u2)Lu1u2, where L is a positive constant, for all tR,u1,u2U. Moreover, υ(t):RU is a Poisson stable function. If the Poisson sequence and period ω are such that the Poisson number κω equals to the zero, then the function G(t,υ(t)) is Poisson stable.

Proof. 

Since κω=0, the Lemma A2 implies that there exists a subsequence tkl, such that tkl0(modω) as l. For simplicity, we assume that the sequence tk itself satisfies the condition tk0(modω) as k. Therefore, G(t+tk,v) uniformly converges to G(t,v) as k, for all tR and vU.

Consequently, for arbitrarily fixed positive number ϵ and a bounded interval I one can find sufficiently large number k such that G(t+tk,υ(t+tk))G(t,υ(t+tk))<ϵ2 for all tR, and υ(t+tk)υ(t)<ϵ2L for tI. Finally, we have that

G(t+tk,υ(t+tk))G(t,υ(t))G(t+tk,υ(t+tk))G(t,υ(t+tk))+G(t,υ(t+tk))G(t,υ(t))G(t+tk,υ(t+tk))G(t,υ(t+tk))+Lυ(t+tk)υ(t)ϵ2+Lϵ2Lϵ,

for all tI. That is, G(t,υ(t)) is Poisson stable function.  □

Lemma A7.

Assume that a function G(t,u):R×URn,URn, is Poisson stable in t and satisfies the inequality G(t,u1)G(t,u2)Lu1u2, where L is a positive constant, for all tR,u1,u2U. Moreover, υ(t):RU is a Poisson stable function. If there exists a Poisson sequence common for the functions G(t,u) and υ(t), then the function G(t,υ(t)) is Poisson stable.

Proof. 

Let us fix a positive number ϵ, and a bounded interval I. Since G(t,v(t)) is Poisson stable in t, and v(t) is Poisson stable function, there exists sufficiently large k, such that G(t+tk,υ(t+tk))G(t,υ(t+tk))<ϵ2 for all tR, and υ(t+tk)υ(t)<ϵ2L for tI. That is,

G(t+tk,υ(t+tk))G(t,υ(t))G(t+tk,υ(t+tk))G(t,υ(t+tk))+G(t,υ(t+tk))G(t,υ(t))G(t+tk,υ(t+tk))G(t,υ(t+tk))+Lυ(t+tk)υ(t)ϵ2+Lϵ2Lϵ,

for all tI. Thus, G(t,υ(t)) is Poisson stable function.  □

Remark A3.

The last lemma implies, in particular, that sum and product of Poisson stable functions with common Poisson sequence are Poisson stable functions.

Appendix B

This part of the paper is about an example of the Poisson stable functions. The task is not an easy one, and there are very few constructively determined cases [4,5]. In our research, we use the dynamical approach of functions determination. One of the most familiar is of sin and cos functions as solutions of ordinary differential equations. We shall consider the Poisson function as a continuous component of solution for a hybrid system, which consists of a discrete equation and a simple differential equation, while discrete component can be accepted as a Poisson stable sequence. A significant element of the present study is visualization of the continuous Poisson stable solution through a neighboring it by an asymptotically close counterpart.

In [6] as a part of the result construction of a Poisson stable sequence was performed as the solution of the logistic equation

λn+1=μλn(1λn). (A1)

More precisely, it is proved that for each μ[3+(2/3)1/2,4] there exists a solution {ηn}, nZ, of Equation (A1) such that the sequence belongs to the interval [0,1] and there exists a sequence ζn, which diverges to infinity such that |ηi+ζnηi|0 as n for each i in bounded intervals of integers.

Consider the following integral

Θ(t)=te2(ts)Ω(s)ds,tR, (A2)

where Ω(t) is a piecewise constant function defined on the real axis through the equation Ω(t)=ηi for t[i,i+1), iZ. It is convenient to consider the function Θ(t) as a unique bounded on the real axis solution of the equation Θ=2Θ+Ω(t). In all next examples of the paper we use the function notation Ω(t)=Ω(μ,q)(t), where q denotes the length of the intervals on which the function Ω(t) is built.

It is worth noting that Θ(t) is bounded on the hole real axis such that suptR|Θ(t)|1/2.

Next, we will show that Θ(t) is a Poisson stable function.

Consider a fixed closed interval [a,b] of the axis and a positive number ε. Without loss of generality one can assume that a and b are integers. Let us fix a positive number ξ and an integer c<a, which satisfy the following inequalities e2(ac)<ε2 and ξ[1e2(bc)]<ε. Let n be a large natural number such that |Ω(3.89,1)(t+ζn)Ω(3.89,1)(t)|<ξ on [c,b]. Then for all t[a,b] we obtain that

|Θ(t+ζn)Θ(t)|=|te2(ts)(Ω(3.89,1)(s+ζn)Ω(3.89,1)(s))ds|=|ce2(ts)(Ω(3.89,1)(s+ζn)Ω(3.89,1)(s))ds+cte2(ts)(Ω(3.89,1)(s+ζn)Ω(3.89,1)(s))ds|ce2(ts)2ds+cbe2(ts)ξdse2(ac)+ξ2[1e2(bc)]<ε2+ε2=ε.

Thus, |Θ(t+ζn)Θ(t)|0 as n uniformly on the interval [a,b].

Author Contributions

M.A.: conceptualization; methodology; investigation. M.T.: investigation; supervision; writing—review and editing. A.Z.: software; investigation; writing—original draft. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data is contained within the article.

Conflicts of Interest

The authors declare no conflict of interest.

Footnotes

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