1. Introduction
Currently, in the context of the digitalization of the economy, strengthening the scientific validity of decisions is becoming more and more relevant. The basis of such strengthening is economic and mathematical methods that implement a targeted approach to solving actual applied problems. This approach allows one to find ways and means to achieve strategic goals, balance the goals and means to achieve them. Here we consider some of the typical problems of economic dynamics in relation to a wide class of hybrid dynamic models with aftereffect. For certainty, the focus is on systems that model the interaction of production processes and procedures of financing them. Recall that an essential feature of any economic processes is the presence of a lag which means a period of time between the moment of external action and a reply of the system, for instance, between capital investments moment and an actual growth in output. Thus a model governing the dynamics of the system under consideration can be written in the form of functional differential system (FDS) with continuous and discrete times (Hybrid FDS = HFDS, for short). The term “hybrid” is deeply embedded in the literature in different senses, that is why we follow the authors employing the more definite name “continuous-discrete systems” (CDS), see, for instance, References [
1,
2,
3,
4,
5] and references therein. In the works mentioned, the reader can find a detailed motivation for studying CDS and examples of applications to problems of controllability, observability and stability. It should be noted that in most cases dynamics in continuous time is governed by ordinary differential systems. Contrary to those we consider a quite general case of continuous subsystems.
After introductory
Section 1 and
Section 2 with necessary preliminaries, we consider three types of problems separately. Boundary value problems (BVPs) are the problems on the solutions to CDS that satisfy some additional (boundary) conditions. From the view-point of Economics, the solvability of a BVP means the existence of a model trajectory with certain property, say, with the periodicity in development. Some sharp sufficient conditions of the solvability for a wide class of periodic BVPs for hybrid systems with deviating argument are presented in
Section 3. The study of control problems (CPs) in the case of the solvability answers the questions of attainable values of on-target functionals and allows one to construct a corresponding programming control with taking into account prescribed constraints. The results on CPs for CDS with polyhedral constraints with respect to control are given in
Section 4.
Section 5 focuses on questions of solutions stability to HFDS as the property of great importance for trajectories defined on unbounded period of time. For a class of hybrid systems, a description of asymptotic properties of solutions is presented.
2. Preliminaries
Our consideration is based in essence on the ideas and results of the theory of Abstract Functional Differential Equation (AFDE) constructed by N.V. Azbelev and L.F. Rakhmatullina in Reference [
6]. AFDE is the equation
with an operator
acting from a Banach space
isomorphic to the direct product
with a Banach space
. The key idea of the AFDE theory applications is in the appropriate choice of
D while studying each new problem. Such a choice allows one to apply standard constructions and statements to the problem needed before an one-off approach and special constructions. This concept has demonstrated the high efficiency as applied to wide classes of problems, see Reference [
7]. Here we follow this concept while studying some urgent problems with respect to hybrid models of economic dynamics.
To give a description of the general form to the model, let us start with the main spaces where the equations are considered.
In description of the systems under consideration we follow Reference [
8].
Fix a segment . By we denote the space of summable functions under the norm , where stands for an arbitrary fixed norm of (we omit the subscript when it does not cause confusion); is the space of square summable functions with the inner product , where stands for transposition.
The space
is the space of absolutely continuous functions
with the norm
Let us fix a set
denotes the space of functions
under the norm
Below we use the symbol z for elements of keeping in mind and . The space of all embedded in by is denoted by .
We consider the hybrid system
where the linear bounded operators
act as follows:
,
,
,
;
. Additionally, operator
is assumed to be compact one (compactness conditions can be found in References [
7] (pp. 43, 284), [
9] (p. 77)). As for the representation of all operators, it will be given more in detail in each section below.
The system (
1) is a particular case of the abstract functional differential equation (AFDE) [
6,
7]. In the sequel we use some fundamental results from the Theory of AFDE. Let us recall some of basic results as those given in Reference [
7].
2.1. From the AFDE Theory
Let D and B be Banach spaces such that D is isomorphic to the direct product (in the sequel we write for short).
A linear
abstract functional differential equation (AFDE) is the equation
with a linear operator
.
We denote by
a linear isomorphism with
. Define the norms in
and
by the equalities
The operator is called the principal part of , is the so-called finite-dimensional part.
Theorem 1 ([
7])
. An operator is a Noether one if and only if the principal part of is a Noether operator. In this case . It follows from Theorem 1 that in the case the operator Q is Fredholm (i.e., it can be represented as a sum of an invertible and a compact operators).
Let be a basis for the kernel of . The vector is called the fundamental vector to the equation with the fundamental system of solutions .
To define a
linear boundary value problem, we introduce a linear bounded vector-functional
with linearly independent components
and consider the system
In the case
,
, the unique solvability of (
3) takes place if and only if
, where
.
Theorem 2 ([
7])
. The problem (3) is a Noether one if and only if the principal part of is a Noether operator and also . Corollary 1 ([
7])
. The problem (3) is a Fredholm one if and only if . In the sequel we consider only the case Q is Fredholm. Thus, for the problem (
3) with
, the assertions “the problem has a unique solution for a certain right-hand part
( the problem is uniquely solvable)”, “the problem is solvable for each
( the problem is solvable everywhere)”, “the problem is everywhere and uniquely solvable” are equivalent.
Theorem 3 ([
7])
. The following assertions are equivalent.- (a)
.
- (b)
.
- (c)
There exists a vector-functional such that the problem (3) is uniquely solvable for each .
Consider the uniquely solvable problem
The solution to (
4) has the representation
where the linear operator
is called the
Green operator.
2.2. Hybrid System as an AFDE
From the view-point of the AFDE Theory, the system (
1) is the Equation (
2) with
defined by the equality
where
. Thus we have here
with
and
. Note also that the operators
and
r are defined by the equalities
To define the principal part
for this case, introduce operators
and
by the equalities
and
. Now we have the representation
Due to the assumption on the compactness of this Q is a Fredholm operator.
3. Periodic Boundary Value Problems
Recently, in a variety of mathematical models (including economic ones), both time lags and advances have begun to be used. Here our review partially follows the review from Reference [
10]. Anticipated backward stochastic equations with a generator depended not only on the solution in the present, but also in the future time were considered in Reference [
11]. In Reference [
12], there were introduced backward equations, the coefficients of which depended on the solution in present and past times. It was natural to consider backward equations, the coefficients of which depend on both the past and future states [
10,
13,
14]. Such equations have been applied in many fields, from finance to stochastic management. In References [
15,
16,
17], mixed functional differential equations were considered in the deterministic case, and some economic applications of such equations were indicated. As a rule, to find conditions for the existence of solutions, the principle of contraction maps or general theorems on fixed points were used.
Economic mathematical models giving rise to mixed functional differential equations are also considered in References [
18,
19]: in production cycle theory the following equation arises
It is clear that this equation is an idealization, and delays and advances are not constant, they are not located in a set of points. More realistic formulations lead to functional differential equations with a general deviation of the argument, the exact laws of change to which cannot be known, as a rule.
We will consider systems of two functional differential equations with general delays and advances. The first unknown variable is an absolutely continuous function defined on a segment of the real axis (a component with continuous time), the second is a component with discrete time, represented as an element of space . Boundary value problems for such systems often arise when considering problems of economic dynamics. We restrict ourselves to considering a periodic boundary value problem that arises, in particular, in the study of business cycles in economics.
Here the space is the space of continuous functions with the norm ; is the set of vectors from with nonnegative components.
We consider the continuous–discrete system
subjected to the periodic-like boundary conditions
where
is a continuous component of a solution;
is a discrete component of a solution;
,
,
,
are linear bounded operators;
, the numbers
,
, and
,
are given.
We suppose that the linear operators
,
,
,
are differences of two positive linear operators:
that means the operators
map nonnegative continuous functions to almost everywhere nonnegative functions, the operators
map elements of
to almost everywhere nonnegative functions, the operators
map nonnegative continuous functions to elements of
, the operators
map
into
.
Problems (
7)–(
9) can always be rewritten in the following way
where
,
, are linear bounded functionals; the coefficients
,
;
,
,
are given. So, the operators
,
are defined by the equalities
where for
we use notation
Together with system (
7)–(
9) (or (
10)–(
12)) we consider a system with continuous time:
where
with
Obviously, there is a one-to-one correspondence between solutions
of problem (
10)–(
12) and solutions
to (
13)–(
15):
Moreover, the equalities
hold, where
is the unit vector from
,
,
, is the unit function from
C.
Further we use only the functions
,
and vectors
,
for formulating our assertions. It follows that we may consider in this section problem (
13)–(
15) instead of problem (
7)–(
9).
3.1. Integral Restrictions on Functional Operators
Theorem 4. Periodic boundary value problem (7)–(9) is uniquely solvable if the conditionsare fulfilled for all real numbers , , , satisfying the conditionsall real numbers , , , satisfying the conditionswhenever the real numbers , , , satisfy the conditions For any given nonnegative numbers , , , , the conditions of Theorem 4 can always be verified by numerical calculations.
Remark 1. Theorem 4 and Theorems 5–8 presented below give sufficient conditions of the unique solvability. In fact, some kind of the necessity takes place. Namely, the proofs implies that these conditions are necessary for the unique solvability of all problems for given numbers , , , .
If diagonal operators
,
are zero or all operators
,
,
,
are positive, we can formulate solvability conditions of problems (
10)–(
12) in closed analytical form (in Theorems 5 and 6). After that we will prove all these theorem together.
Theorem 5. Let , , , . Then periodic problems (7)–(9) is uniquely solvable ifandwhere . Theorem 6. Let , , , . The periodic boundary value problems (7)–(9) is uniquely solvable ifor Proofs of Theorems 4–6. These theorems have been proved by a unified scheme. For the corresponding problems (
7)–(
9) with continuous time, these assertions are proved in References [
20,
21] for Theorems 4 and 6 and in Reference [
22] for Theorem 5. There are one-to-one correspondences between solutions of problem (
13)–(
15) with continuous time and the corresponding problems (
10)–(
12) from Theorems 4–6. In References [
20,
21,
22], we used only the functions
,
,
,
for proving of sufficiency. As for proving of necessity, it was used only operators of the form (
16) and (
17) in References [
20,
21,
22]. From equalities (
19), it follows that the assertions of the theorems and Remark 1 are valid for hybrid systems too. □
Remark 2. Condition (26) is fulfilled if In the symmetric case , the minimum in (26) occurs at . Therefore, condition (26) means that In the case , it is easy to check that the minimum in (26) occurs at So, if , we can obtain the minimum in (26) analytically. In particular, we have the following sufficient condition: (26) is fulfilled if Conditions (27), (28) are obtained in Reference [21]. Because the norms of the functions and , and , and coincide, we can use these results from Reference [21] for hybrid systems. To derive condition (29) from condition (26), we need only to check the elementary inequality with the polynomial of degree 4 in and t:for all , , where F is the right-hand side in (29). Remark 3. From Reference [21] it follows that the assertion of Theorem 6 is valid for every problem of the formwhere , , . 3.2. Point-Wise Restrictions on Functional Operators
Let nonnegative numbers , , , be given.
First we consider problems (
7)–(
9) only with positive operators and under more general point-wise restrictions than conditions (
40) in the next theorem, where, however, the operators can be differences of positive operators.
We suppose (without loss of generality) that there exist a positive function
and a vector
with positive components such that
and there exist nonnegative numbers
,
,
,
such that
Denote , .
Theorem 7. Let , , , and conditions (30), (31) be fulfilled. Ifthen periodic boundary value problem (7)–(9) is uniquely solvable. Proof. It is more convenient to deal with continuous systems. Thus we consider the system
with positive operators
such that
where
for
,
.
By all the above arguments, it suffices to prove the statement only for problems (
33)–(
35) with continuous time.
Let the homogeneous problems (
33)–(
35) (for which
,
) have a non-trivial solution
and
Suppose , (if it is needed, we renumber and , ).
By Lemma 3.3 [
20] (p. 216) (or Lemma 1 [
21]) we have
for some functions
,
,
, such that
,
,
,
.
From (
37) it follows that the numbers
,
,
,
satisfy the following algebraic system:
We can exclude variable
and
and obtain a system of four equations in four unknowns:
Further we use the notation:
,
,
,
. Obviously, system (
38) has a non-trivial solution if and only if the following determinant
vanishes:
where
Thus, the variables , may take any value from the interval ; , from the interval ; , from ; , from independently. Here and take all values from the interval also independently.
Now to prove the assertion of the theorem we have to show that
for all admissible values of parameters
,
,
,
,
,
,
,
,
,
. Then the homogeneous problem has no non-trivial solutions. Therefore, by the Fredholm property (see
Section 2.2) problem (
33)–(
35) is uniquely solvable.
For admissible values
, we have
. Therefore, the condition
is the first necessary condition of the unique solvability.
Since
and
is continuous in all its parameters, we see that
must preserve its sign for all admissible values of parameters. Since
is linear in every variable
,
,
,
,
,
,
,
, we have to consider
for all these variables at the ends of admissible intervals. There are 8 such variables, therefore, we have to consider 256 cases. However, all these cases can be reduced to only 16: the ratio
may take the following values
where
Therefore, if and only if the problem is uniquely solvable, all these values are negative. From inequalities
,
, we obtain that
and
. As to the rest inequalities, it is enough to verify the inequalities
These inequalities are fulfilled for all
if and only if
Therefore, the assertion is proved both for problems (
7)–(
9) and for problems (
33)–(
35). □
Now we formulate solvability conditions for a boundary value problem with arbitrary operators
,
,
,
satisfying the following equalities for given non-negative constants
,
,
,
:
Theorem 8. Let conditions (40) be fulfilled. Ifthen periodic problems (10)–(12) is uniquely solvable. The scheme of the proof is the same as in Theorem 7, where the factors p, q are chosen constant. We omit the complete proof due to its cumbersomeness caused by the need to consider both the positive and negative parts of the operators. It is important that the form of necessary and sufficient conditions turns out to be similar to conditions for the case of positive operators.
3.3. A Nonlinear Case
It Theorems 4–6, we obtained conditions for uniqueness and existence of periodic solutions in the linear case. Here we find non-existence conditions for the nonlinear system (see other results on similar nonlinear problems in References [
23,
24])
where
,
.
We impose on the operators some kind of the Lipschitz conditions:
there exists a constant
such that for every
the following inequality holds
there exists a constant
such that for every
the following inequality holds
there exists a constant
such that for every
the following inequality holds
there exists a constant
such that for every
the following inequality holds
It should be noted that under some natural conditions the product of the Nemytskii operator [
7] (p. viii) and the inner superposition operator [
7] (p. 93) satisfies these conditions.
The following theorem describes conditions under which non-constant business cycles become impossible whenever the nonlinear functional operators of system have point-wise restrictions.
Denote , , , .
Theorem 9. If the inequalitiesare fulfilled, then problems (43)–(45) under conditions (46)–(49) has no non-constant solutions. Proof. From conditions (
46)–(
49), it is easy to see that if a pair
is a solution of periodic problems (
43)–(
45), then this pair is a solution of some linear non-homogeneous problem
for some constants
, where positive linear operators
,
,
,
satisfy conditions (
40). From (
50) and Theorem 8, it follows that this problem has a unique solution. It is clear in this case, that both components of the solution
x and
z are constants. □
4. Control Problems
Let us recall the general formulation of the control problem as applied to the hybrid system under control
with an operator
defined by the equality (
5) and control
with components from the Hilbert space
of square summable functions
equipped with the inner product
(as usually,
);
is a linear bounded Volterra [
7], ([
9] p. 106) operator,
. The initial state of the system (
51) is assumed to be fixed:
The aim of control is prescribed by the equality
where
is a given linear bounded vector-functional.
We say that the control problems (
51)–(
53) is solvable by a control
u if the trajectory
generated by
u, brings the prescribed value
to the on-target vector-functional
ℓ.
4.1. General Results
Within this subsection, we consider the hybrid system (
51) with operators
defined as follows.
Here the elements
of the kernel
are measurable on the set
and such that
,
is summable on
, the
-matrix
has elements summable on
.
where elements of matrices
are summable on
. As it usually is, here and in the sequel
for any
if
.
with measurable and essentially bounded on
elements of matrices
and constant
-matrices
.
with constant
-matrices
.
This system is a special case of the general continuous-discrete system considered in detail in Reference [
25]. Theorem 1 [
25] gives the representation of the general solution in the form
where
,
are the fundamental matrix and the Cauchy operator respectively. The block-components
,
,
, are operators acting as follows:
It should be noted that, with respect to the continuous time component
, we restrict ourselves to the case
and so ignore the impulsive component of the solution [
25].
The general results on the solvability of (
51)–(
53) from Reference [
8] are based on the following approach. The representation of the linear bounded vector-functional
has the form
where
-matrix
and
-matrices
are constant, and
-matrix
have measurable and essentially bounded elements. The general form of
ℓ covers many various special cases used while studying applied problems (see, for instance, Reference [
26]). Here we restrict ourselves to the following example of (
53):
Using the representation (
55) and the description of the set of all trajectories to the system under control
we can express the on-target conditions (
53) in the form that is explicit with respect to the control
:
or, denoting
as the system
with respect to
u. The solvability of (
58) means the controlability of the hybrid system (
51) with respect to the on-target vector-functional
ℓ. In the case we consider, (
58) may be reduced to the form
where
-matrix
is called the moment matrix to the problems (
51)–(
53). The justification of all transformations from (
58) to (
59) with an explicit form of
requires the deep study of the Cauchy operator properties which is done in Reference [
25]. The system (
59) opens a way to construct controls that provide the solutions to (
51)–(
53). In particular, a control can be found in the form
with a constant
N-vector
d (
stands for transposition). In such a case, we obtain the linear algebraic system with respect to
d:
where
Thus we obtain the condition
for the solvability of (
51)–(
53). This condition is well known for many special classes of dynamic models with continuous and discrete times as applied to the very specific kind of the on-target vector-functional
ℓ when
. General results on the controlability of hybrid models with sufficient conditions and description of the programming control bringing the prescribed values
are presented in Reference [
8]. It should be noted that possible constraints with respect to control, which are met in real world economic dynamics problems, are ignored in the formulation (
51)–(
53). Thus the results mentioned relate to the problems with unconstrained control. For a class of hybrid models, the case of constrained control where constraints are defined by a finite system of inequalities is considered in the next subsection.
4.2. Constrained Control of Hybrid Systems with Discrete Memory
In applied control problems with prescribed on-target indexes, a central place is occupied by constraints with respect to control. The rigidness of constraints impacts essentially onto the solvability of the problem that is the existence a control such that the trajectory generated by it brings the prescribed targeted values. Description of all values attainable under the action of controls with fixed constraints is one of the key problems in the frames of various control theory divisions (see, for instance, References [
27,
28,
29,
30,
31]), including questions of the attainability set structure under various classes of constraints [
32,
33], their asymptotic [
34] and statistical characteristics [
35,
36]. Therewith, as a rule, the attainability is understood with respect to the state of the system at a given instant. In control problems for economic systems, a more general point of view takes place when on-target indexes are given as integral characteristics and multipoint ones. Here we set the on-target indexes with the use of linear functionals having the general form that covers above mentioned cases. The system dynamics is described by the union of differential equations with delay and difference equations with discrete time. Such a description turns out to be urgent as applied to economic dynamics processes with interactions of variables having disparate kinds of changes, namely, continuous (say for production process) and discrete (say investment or financing). We pay the most attention to the external estimates of attainability sets with corresponding relationships and algorithms. The results are based on the general theory of functional differential equations [
7] in terms of the solvability conditions and the representation of solutions, as well as on some of our previous results [
25,
26,
37,
38]. Here we recall some results on estimating attainability sets and propose estimates of switch points number to programming control for systems with discrete memory.
We consider the economic-mathematical model of interaction of the production subsystem
and the financial subsystem
with summable
-matrices
,
-matrices
and constant
-matrices
,
- matrices
.
For definiteness, we consider
in (
60) as indexes (state variables) of functioning of a multiproduct productive system that change in continuous time
. The rate of change depends on the productive accumulation at fixed points in time,
with a given effectiveness (by elements of
). In addition, there are used investments
governed by (
61). The integral term in (
60) simulates the direct control
of the indexes dynamics of
with an effectiveness defined by the kernel
. The right-hand side of (
61) includes at each
the previous investment values
, the productive accumulation, as a part of
, and the control
as a financial flow density. Therewith the integral term takes into account financial resources accumulated at
. The effectiveness of the use to all above factors is given by the matrix coefficients
. The functions
and
can be interpreted as external actions or disturbances, say, unforeseen lost or modeling errors. It should be noted that the specific kind of delay in (
60) is of considerable current use as applied to dynamic economic models [
39]. As in the general case, the initial state of (
60) and (
61) is assumed to be fixed:
Using (
55), we define the aim of control by the equality
where
is a given vector of on-target values.
The problem of getting the values prescribed by (
63) is considered with the constraints concerning control:
where
is a given constant
-matrix. The set of solutions to the linear inequalities system
is denoted by
and assumed to be nonempty and bounded.
As is noted in the previous subsection, we reduce the problems (
61)–(
64) to the moment problem
where
, with the polyhedral constraints (
66).
Having in mind that the Cauchy operator
to (
61) and (
62) can be found in the explicit form [
38], we give here the representation of the moment matrix
in the terms of components
To do this, we shall use the representation of the solution to (
61) and (
62) in the case
:
Next we obtain the expression for
, taking into account the properties of the kernel
:
or, after some evident transformations,
where
Finally, after substitution of the right-hand sides of (
67) and (
69) into the representation of
we arrived at the representation of the matrices
that form
:
Let us recall the results on estimates of the
ℓ-attainability sets from Reference [
37].
For any
, define
by the equality
In the case that the extremal value in (
70) is reached at a number
m of angle points
of the polyhedron
, we understand
as
By Theorem 1 [
37], the set of all attainable
in (
65) and (
66) is the set of all
such that the inequality
holds for any
.
Let us describe a way to obtain an internal estimate of the set of all attainable
in (
65) and (
66). Fix a collection
and a collection
,
. Define the control
by the equality
where
. There takes place the following assertion.
Theorem 10. Let the elements of the moment matrix be piecewise continuous. Put Then the convex hull of is a subset of the set of all attainable in (65) and (66). Proof. By construction of the controls
those are admissible, and their convex hull is a subset to the set of all admissible controls. Any
is attainable by the control
. Let
where
Then we have
and, hence,
is attainable by the control
This completes the proof. □
In applied problems, the question of a switch points number to the control bringing the prescribed on-target indexes is of special interest. A true number of switch points is defined by (
70) and (
71) and does depend on
and
. An illustration is given in the next subsection.
4.3. An Example
Consider the system under control
with the initial conditions
the constraints with respect to control
and the on-target conditions
With the use of the results [
25] on the Cauchy operator we construct the moment matrix
that corresponds to the on-target functional:
Here the numerical coefficients are displayed to six places of decimals.
In this case we find the following three points:
forming the triangle that is a subset of the attainability set and contains the given point
from the on-target conditions. That point is the convex linear combination of the above three points with the coefficients
respectively. Having in mind that the controls bringing P2 and P3 has two switch points
and
, and
is attainable by
, we conclude that the problem under consideration may be solved by the control with two switch points.
5. Stability and Asymptotic Behavior of Solutions
The currently constructed theory [
7] permits the clear description of main properties of FDEs, among them the stability properties of solutions [
40], whereas many relevant classes of HFDEs are not encompassed by the constructed theory and are beyond the attention of experts employing systems with aftereffect while modelling real-world processes. Hybrid analogs of the main statements of the FDEs theory concerning stability questions are proposed below.
5.1. The Scheme of N. V. Azbelev’s W-Method as Applied to Hybrid Models
Let us first consider the case when one equation is a linear functional differential equation with aftereffect on the semi-axis, and the other is a linear difference equation, and describe for this case the scheme of N. V. Azbelev’s W-method.
Introduce the space
L as the space of locally summable functions
with semi-norms
for all and the space locally absolutely continuous functions
with semi-norms
for all
. Denote by
the infinite matrix with the
-columns z(-1), z(0), z(1), ..., z(N), ... and, analogously,
will stand for the infinite matrix with the
-columns
,
. By any
z we define the function
:
and by any
g define the function
:
In the sequel we denote and where is the integer part of t. Let be the space of functions with semi-norms for all integer , and ℓ be the space of functions with semi-norms for all integer .
Further, define , .
Consider the hybrid functional differential system
For convenience, let us introduce operators
:
The operators
are assumed to be linear continuous and Volterra. Denote
. Then (
75) takes the form
.
Let
be a model system such that, for any
and
, the Cauchy problem be uniquely solvable (as for operators
, we save the same assumptions as to
). The model system may be written in the form
. Its solution has the representation
where
is the Cauchy operator,
;
is the fundamental matrix,
If elements
constitute a Banach space
(
are Banach spaces) and possess certain specific properties, say,
and the Cauchy problem for an equation
with a linear bounded operator
is uniquely solvable, then its solutions have the same asymptotic properties. This follows from the following theorem [
41].
Theorem 11. Let be the bounded Cauchy operator to a model problem with , and is the fundamental matrix to . Let, further, a linear operator be bounded, C is the Cauchy operator to , and X is its fundamental matrix. Then the equality holds if and only if the operator has the bounded inverse .
Corollary 2 ([
41])
. If an operator is bounded and the inequality holds, then the equality (76) takes place. In the case of equality (
76) (the coincidence of the solution space of the model and the studied equations), we say that the equation
has the property
or, for short: the equation is
-stable. We note the connection of the concept of
-stability with the monograph by J. L. Massera and J. J. Schaffer on the admissibility of pairs of spaces [
42], and with the monograph by E. A. Barbashin on preserving the properties of solutions when perturbations accumulate [
43]. Let the model equation [
7,
44,
45,
46]
and the Banach space
with elements from the space
L (recall that
and this embedding is continuous) be chosen so that the solutions of this equation have the asymptotic properties that are of interest to us.
For example, let
be hold. Then, putting
, we take as
the Banach space
of measurable and essentially bounded functions
with the norm
. The space
generated by the model equation consists of the solutions
that are bounded (
) and have the derivative
from
.
All these solutions form the Banach space equipped by the norm
This space is isomorphic to the Sobolev space
with the norm
In the sequel we denote this space by , note that and the embedding is continuous.
Similarly, introduce the space
,
, with the norm
Under natural conditions [
40,
44,
45,
46], the space
is isomorphic to the Sobolev space
with the norm
which we denote by
.
The equation
with an operator
is
-stable if and only if it is strictly
-stable, namely, for any
, every solution
x to this equation possesses the property:
and
[
40,
45].
5.2. The Case of Two Scalar Equations
Let us apply the scheme of
Section 5.1 to the case of two scalar Equation (
75). The operators
are considered as operators of reducing to the pairs
and
under the assumption that the operators are linear bounded and Volterra and the general solution of the equation
, where,
belongs to the space
and has the representation
where
.
Then every solution
z to the second equation in (
75) may be written in the form
After substitution this expression into the first equation of (
75) we obtain
or
Now, putting
, rewrite this equation in the form
. In the case when the Volterra operator
is invertible and the inverse is Volterra too we have that, for any
, the corresponding solution
of (
75) is from the space
.
Example 1. Consider the equationsassuming thatIntroduce the spaces Define the operator S by the equalities ; , then the second equation takes the form As is known, the operator has the bounded inverse if and only if the spectral radius is less than one, or, which is the same, the inequality holds. Let Construct the Cauchy function and the fundamental solution to the equation Now express from the second equation of (77): After substitution this into the first formula of (75) we obtain It is clear that if Write the Cauchy formula as applied to the equation : Here we have , For the case of a positive a, the estimateshold. Therefore, the norm of is less than 1 if , and under this condition we have that, for any , the solution x of belongs to the space together with its derivative . Thus it is established that, for any , solution x to belongs to the space . Therefore, for Equation (77), we obtain the conditionsunder which, for any , solution of it belongs to the space . 5.3. A Case of Periodic Parameters: Direct Study of Asymptotic Behavior
The case of economic dynamic models with periodic parameters is of special interest [
47].
Here we consider a hybrid model with short discrete memory and demonstrate a way to study asymptotic behavior of solutions, namely, the existence of a finite limit state of the system as .
Consider the system
with 1-periodic matrices
and
of the dimensions
and
respectively, constant matrices
D and
H of the dimensions
and
, respectively, 1-periodic functions
and a given initial state:
Define the constant matrices
by the equalities
and the
-matrix
by the equality
where
is the identity
-matrix.
Theorem 12. Let the spectral radius of be less than 1. Then there exists a vector with finite components such that the solution of the problems (79) and (80) possesses the property Proof. Let us integrate the first equation of (13) from
to
,
:
Put
, then we have
where
. By the assumptions, the successive approximations (
81) converge to
y being the solution of the system
□
Example 2. Consider the systemwhere with the initial state defined by the equalities For the case, we have , As for the limit state y, its approximate value after 50 iterations is (the components are displayed to nine decimals).