- Open Access
Lower and upper estimates of solutions to systems of delay dynamic equations on time scales
© Diblík and Vítovec; licensee Springer. 2013
- Received: 6 September 2013
- Accepted: 5 November 2013
- Published: 27 November 2013
In this paper we study a system of delay dynamic equations on the time scale of the form
where , and , , are the delay functions. We are interested in the asymptotic behavior of solutions of the mentioned system. More precisely, we formulate conditions on a function f, which guarantee that the graph of at least one solution of the above-mentioned system stays in the prescribed domain. This result generalizes some previous results concerning the asymptotic behavior of solutions of non-delay systems of dynamic equations or of delay dynamic equations. A relevant example is considered.
- time scale
- dynamic system
- asymptotic behavior of solution
1.1 Time scale calculus
Time scale calculus, first introduced by Stefan Hilger in his PhD thesis in 1988 (see ) is nowadays well-known calculus and often studied in applications. Recall that a time scale is an arbitrary nonempty closed subset of reals. Note that (resp. etc., we define any combination of right and left open or closed intervals), , σ, ρ, μ and stand for the finite time scale interval, infinite time scale interval, forward jump operator, backward jump operator, graininess and Δ-derivative of f. Further, we use the symbols and to stand for the class of rd-continuous and rd-continuous Δ-differentiable functions defined on the time scale . Finally, we work with all types of points on the time scale , i.e., with right-dense points or right-scattered points, respectively with left-dense points or left-scattered points. See , which is the initiating paper of the time scale theory, and  containing a lot of information on time scale calculus.
Now we remind further aspects of time scales calculus, which will be needed later (see, e.g., ). We use the standard symbol for an arbitrary vector norm. Note that (in this paper) a type of a norm is not important.
rd-continuous if g defined by is rd-continuous for any rd-continuous function ;
- (ii)bounded on a set if there exists a constant such that
- (iii)Lipschitz continuous on a set if there exists a constant such that
1.2 System of delay dynamic equations on time scales
on the time scale .
then we say that y is a solution of initial problem (IP) (1), (2).
1.3 Existence and uniqueness of solutions of delay dynamic equations
For the next study, it is important to known whether a solution of IP (1) and (2) exists and if it is uniquely defined. However, the following theorem (in a more general form) can be found in [, Theorem 2.1].
Theorem 1 (Picard-Lindelöf theorem)
Carefully tracing the proof of Theorem 1 in , it is easy to verify that if Theorem 1 holds, then the solution of IP (1), (2) depends continuously on the initial data.
This condition says that, by Theorem 1, every initial problem (1) and (2) with φ satisfying (3) has exactly one solution on an interval where . It is also easy to show that this solution depends continuously on the initial function φ.
Throughout the paper, we assume that the function f is bounded and Lipschitz continuous on an open set S and , which implies that every initial problem (1) and (2) has exactly one solution on an interval .
The aim of this paper is to establish sufficient conditions on the function f of equation (1) such that there exists at least one solution of (1) defined on such that for each . The main result generalizes some previous results of the first author (and his co-authors) concerning the asymptotic behavior of solutions of discrete and dynamic equations (see, e.g., [5–9]).
In papers [5, 6], to our best knowledge, the retract principle is for the first time extended to discrete equations. In  delayed discrete equations are considered by retract technique, and in  the retract principle is given for discrete time scales. Paper  is devoted to extension of the retract principle to dynamic equations. In  the retract principle is extended (under different conditions) to a system of dynamic equations in the plane. In  we extended the retract principle to scalar delayed dynamic equations. In the present paper we give an attempt to enlarge the retract principle to systems of delayed dynamic equations.
2.1 Points of strict egress
where . Obviously, .
From the definition of Δ-derivative and the property , we get (or ) for with a small positive δ if is a right-dense point and for if is right-scattered.
is a point of strict egress for the set Ω with respect to (1) and is a (unique) solution of (1) satisfying , then, due to (5), (or ) for with a small positive δ if is a right-dense point and for if is right-scattered.
We see that in all the cases considered, the solution of (1) with the initial condition , , and satisfies for with a small positive δ if is a right-dense point and for if is right-scattered.
Definition 3 
If are subsets of a topological space and is a continuous mapping from B onto A such that for every , then π is said to be a retraction of B onto A. When a retraction of B onto A exists, A is called a retract of B.
The following theorem is proved by utilizing the idea of a retract method, which is well known for ordinary differential equations and goes back to Ważewski . In the next theorem, we assume that the function f, except for the indicated conditions, satisfies all the assumptions given in Section 2. Namely, we assume that the function f is bounded and Lipschitz continuous on an open set S and .
Proof The idea of the proof is the following. By contrary, we assume that a solution y satisfying (8) does not exist. Then we are able to prove (by a construction of a chain of auxiliary mappings) an existence of a retraction of an n-dimensional ball into its boundary. However, it is well known that the boundary of an n-dimensional ball cannot be its retract (see, e.g., ) and we get a contradiction.
with having the value defined above except for the case . In the latter case, we put .
if , where and are as above.
Note that if , we get the particular case and .
It is easy to see that the is a retract of and satisfies all the assumptions from Definition 3 (with and ).
Suppose now that (which is equivalent to ). We consider all the possible settings of and characters of .
Further, is also continuous because of the continuity of mappings and .
Hence the composite mapping is continuous. Further, is also continuous because of the continuity of mappings and . The alternative with can be proved by the same limit process as in the first case, where the point is dense.
Hence the continuity of is proved. Further, is also continuous (for the same reason as before).
Fourth, suppose now that is an isolated point, i.e., . Let, as before, (11), (12) and (13) hold. Then, for sufficiently small δ, we have either (if ) or (if ). Without any special comment, in the alternative , we proceed in the same way as in the second case, where is left-scattered and right-dense. Furthermore, in the alternative , we proceed in the same way as in the third case, where is left-dense and right-scattered.
Hence the composite mapping is continuous. Moreover, is also continuous because of the continuity of mappings and .
We proved that the composite mapping is continuous. Note that we omitted the special case (which is equivalent to ). However, this part can be shown in an analogous and simpler way to the one used above.
is an identity mapping. In this situation, we have proved that there exists a retraction of the set B onto the set A (see Definition 3). In view of the above-mentioned fact, this is impossible. Our assumption is false and there exists initial problem (7) such that the corresponding solution satisfies (8) for every . The theorem is proved. □
Let, moreover, , and .
is a point of strict egress for the set Ω with respect to the dynamic system (14), (15).
In view of Definition 2, every point is a point of strict egress for the set Ω. Therefore, all the assumptions of Theorem 2 hold and there exists an initial value function with property (16) such that the initial problem defines a solution y on the interval of dynamic system (14), (15) satisfying inequalities (17) for every . This solution (due to (17)) tends to zero as .
Remark 2 Note that the choice in the previous example is not important, and system (14), (15) can be considered on an arbitrary time scale with (it means that there exists such that for each ). Indeed, let us slightly modify the previous example. Consider system (14), (15) on an arbitrary time scale with . (For example, with satisfies this condition.) Let, moreover, , with , . Then one can show that all calculations used in the previous example are true for sufficiently large .
The difference between delay dynamic equations and non-delay dynamic equations (resp. a system of delay dynamic equations and a system of non-delay dynamic equations) with respect to controlling their solutions is as follows. The conditions on the function f to get a bounded solution in a ‘delay’ case are a little bit harder than in a ‘non-delay’ case. More precisely, the bigger the delays are, the harder it is to construct a set Ω of considered equations to get a bounded solution . The reason is that in a delay case the history of solutions plays an important role and influences conditions for points, which are strict egress with respect to the investigated equation. It corresponds to the form of Definition 2, where functions have to satisfy some conditions before they touch or pass the boundary of the set Ω.
A further possible complication in dynamic equations (resp. a system of dynamic equations) - the graininess of the time scale - was discussed in . Moreover, it is obvious that the bigger the graininess is, the bigger the delays are. This fact also implies a problem to control the solution to stay in domain Ω.
Finally, let us consider initial problem (1), (2) with for every . In this case, we get a non-delay dynamic system and the initial function φ defined in (2) can be replaced by the initial condition . Moreover, in this case, carefully tracing the proof of Theorem 2, we can observe that it does not need any change. Hence we can say that Theorem 2 generalizes a result given in  as well.
The first author was supported by Grant No. P201/10/1032 of Czech Grant Agency (Prague). The second author was supported by the project CZ.1.07/2.3.00/30.0039 of Brno University of Technology. The work of the first author was partially realized in CEITEC - Central European Institute of Technology with research infrastructure supported by the project CZ.1.05/1.1.00/02.0068 financed from European Regional Development Fund.
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