![MathJax Logo](/templates/jsp/_style2/_tandf/pb2/images/math-jax.gif)
Abstract
In this paper, we give some new necessary and sufficient conditions for the asymptotic stability of a class of time–delay systems of the form where
is a real number,
is a
real constant matrix, and
,
are positive numbers such that
.
PUBLIC INTEREST STATEMENT
In this paper, asymptotic stability of a class of time–delay systems was investigated. This system is a generalized version of modeling compound optical resonators by using a matrix instead of a scaler. In addition, since asymptotic stability is an interdisciplinary material, the asymptotic stability of these systems has a wide range of applications as biology, physics and medicine.
We know that for the time–delay equations, an equation is asymptotically stable if and only if all roots of the associated characteristic equation have negative real parts. Stability analysis, however, does not require the exact calculation of the characteristic roots. This analysis can be performed by D-subdivision method, which gives a necessary and sufficient condition for stability based on the coefficients or delay parameters of the characteristic equation. Thus, this method reveals a qualitative approach in order to prove the asymptotic stability of the systems. Consequently, we have created new necessary and sufficient conditions for the systems, which are asymptotically stable.
1. Introduction
In this paper, we study the asymptotic stability of the solutions of time–delay systems of the form
where is a real number,
is a
real constant matrix, and
,
are positive numbers such that
. Time–delay systems are a type of differential equations in which the derivative of the unknown function at a certain time is given in terms of the values of the function at previous times. Also, they are called delay differential equations, retarded differential equations or differential-difference equations. On the other hand, since asymptotic stability is an interdisciplinary material, the asymptotic stability of these systems has a wide range of applications as biology, physics, and medicine. For instance, Naresh, Tripathi, Tchuenche, and Sharma (Citation2009) formulated a nonlinear mathematical model to study the framework of disease Epidemiology. As another example Ikeda and Watanabe (Citation2014) were investigated the stochastic differential equations and diffusion processes in their study about physic. Kruthika, Mahindrakar, and Pasumarthy (Citation2017) were studied stability analysis of nonlinear time–delayed systems with application to biological models. They analyzed the local stability of a gene-regulatory network and immunotherapy for cancer modeled as nonlinear time–delay systems.
Many authors have also focused on the asymptotic stability of time–delay systems. Some important studies about related subject can be examined from the below authors: Bellman and Cooke (Citation1963), Cooke and Grossman (Citation1982), Cooke and van den Driessche (Citation1986), Stepan (Citation1989), Freedman and Kuang (Citation1991), Kuang (Citation1993), Ruan and Wei (Citation2003), Elaydi (Citation2005), Matsunaga (Citation2008), Smith (Citation2010), Gray, Greenhalgh, Hu, Mao, and Pan (Citation2011), Khokhlovaa, Kipnis, and Malygina (Citation2011), Xu (Citation2012), Hrabalova (Citation2013), Nakajima (Citation2014), Liu, Jiang, Shi, Hayat, and Alsaedi (Citation2016), and Li, Ma, Xiao, and Yang (Citation2017). Also, an equation which is the special case of our system which is investigated by Kuang (Citation1993) and he demonstrated that the zero solution of the delay differential equation with two delays of the form
where ,
and
is positive constant and is asymptotically stable if and only if
2. Preliminaries
It is known that for the time–delay equations, an equation is asymptotically stable if and only if all roots of the associated characteristic equation have negative real parts. Stability analysis, however, does not require the exact calculation of the characteristic roots; only the sign of the real part of the critical root must be determined. This analysis can be performed by D-subdivision method (see, e.g., Insperger & Stépán, Citation2011; Stepan, Citation1998), which gives a necessary and sufficient condition for stability based on the coefficients of the characteristic equation. The aim of this paper is to obtain new results for the asymptotic stability of zero solution of system (1.1), while the characteristic equation of system (1.1) has roots on the imaginary axis when is a constant matrix. If we obtain
for a regular matrix
in (1.1), then we have the following system:
Thus, matrix can be given one of the following two matrices in Jordan form
:
Here we consider the case the other case should be considered similarly. The characteristic equation of system (1.1) is given as
where is the
identity matrix. Using
we obtain
If we let
then we have
where is the complex conjugate of any complex
Note that
implies
3. Some auxiliary lemmas
In this section, we will investigate the distribution of the zeros of the characteristic equation of system (1.1). Thus, we state and prove some basic results on the roots of the characteristic equation of system (1.1).
Lemma 1 (Stepan, Citation1989) The zero solution of (1.1) is asymptotically stable if and only if all the roots of equation
Lie in the left half of the complex plane.
Since is an analytic function of
and
for the fixed numbers
and
one can regard the root
of (3.1) as a continuous function of
and
The next lemma plays very important role for the main theorem.
Lemma 2 (Cooke & Grossman, Citation1982) As and
vary, the sum of the multiplicities of the roots of (3.1) in the open right half-plane can change only if a root appears on or crosses the imaginary axis.
Consequently, we claim that (3.1) has only imaginary roots . We will determine how the value of
and
change as Equation (3.1) has roots on the imaginary axis. Now, we can write the characteristic Equation (3.1) as follows:
At the same time, we take such that
Firstly, since
we see that
For
, we obtain
Using the real part and the imaginary part of (3.3)
which is equivalent to
is obtained.
Lemma 3. Suppose that, and
Let
be a root
where
for
, then the following conditions hold:
If
then there exists no real number
.
If
then the real numbers
and the delays
are as follows:
and
for
where
and
and or
is a root of
for the sum of delays
or
Proof. By squaring both sides of (3.6) and (3.7), and adding them together, we obtain
If , then statement (3.8) implies
contradicts with
Since
, condition
is verified; that is, (3.1) has no root on the imaginary axis for all
On the other hand, if statement
implies that
If we let
then we can write . By (3.7), we have
Now, we will show that is a root of (3.1).
In the case of since
for
and using
is obtained. Thus, we use (3.6) and (3.7), we have
which yields Also, from (3.6) and (3.7), we obtain
because of
Hence, for the case
is a root of (3.1). Indeed,
Thus, this implies that is a root of (3.1). Similarly, in the case
it can be shown that
is a root of (3.1) for the sum of delays
The proof is completed.
When we have the following analogous result.
Lemma 4. Suppose that, and
Let
be a root of (3.1) where
for
, then the following conditions hold:
If
then there exists no real number
.
If
then the real numbers
and the delays
are as follows:
and
for
, where
and
and or
is a root of (3.1) for the sum of delays
or
Proof. The proof is similar to Lemma 3.
Remark 1. For , from the definitions of
is obtained. Similarly, for ,we obtain from the definitions of
as follows:
Lemma 5. Suppose that
and
Also, the following conditions
are provided. Then all the roots of Equation (3.1) on the imaginary axis move in the right half-plane as and
increase.
Proof. Let be a root of (3.1) where
is a real number. It will be enough to show
Firstly, we take the derivative of with respect to
on Equation (3.1), we have
Substituting into the above equation, we obtain
If we multiply with the complex conjugate of the denominator in the above equation, then we can write
where
Since (3.11), we can write On the other hand, we take the derivative of
with respect to
on Equation (3.1), similar to (3.12)
is obtained. From (3.11), we obtain Moreover, by adding both (3.12) and (3.13) together, we have
Hence, the proof is completed.
Now we can state and prove main theorems.
4. Main results
We will show that the stability analysis with a qualitative approach, as we have already mentioned in section 1.
Theorem 1. Suppose that and the conditions of Lemma 5 are satisfied. Let the matrix A of system (1.1) be in the form
. Then system (1.1) is asymptotically stable if and only if either
or
Proof. In the case of and
the root of (3.1) is only
Thus, the root of the Equation (3.1) has a negative real part. By the continuity of the roots with respect to
and
we can say that all the roots of (3.1) lie in the left half plane for
and
sufficiently small.
For the sufficiency, here our claim is: If either condition (4.1) or (4.2) holds, then (3.1) does not have a root on the imaginary axis. By condition (4.1) and Lemma 3, our claim is true for and
Now, suppose that condition (4.2) holds: Since
and Remark 1, we obtain ,
for
Thus, we obtain the contraposition with Lemma 1, our other claim is also true. By the above argument and Lemma 2, we can say that if either condition (4.1) or (4.2) holds, then all the roots of (3.1) lie in the left half plane.
For the necessity, we will show the following contraposition: either
or
Thus, if (4.3) and (4.4) hold, then there exists roots of (3.1) such that
for
Assume that (4.3) holds and let
be the branch of the root of satisfying
Then, Lemma 5 or the continuity of
implies that
for
and
sufficiently small. From here, we can say that
cannot move in the left half-plane crossing on the imaginary axis as
and
increase. Hence, we have
for all
and
Assume that (4.4) holds and let
be the branch of the root of satisfying
Then, Lemma 5 or the continuity of
implies that
for
and
sufficiently small. From here, we can say that
cannot move in the left half-plane crossing on the imaginary axis as
and
increase. Hence, we have
for all
and
The proof is completed.
Remark 2. We consider the delay differential system (1.1) where matrix A is given as in case , i.e.,
Then, characteristic equation of (4.5) is as follows:
It is obvious that for and
, the equation
is the characteristic equation of (4.6) with
, and so one can immediately obtain the following corollary from the previous result given by Kuang (Citation1993).
Corollary 1. Suppose that for system (4.6) Let the matrix A of system (4.6) is written as the form
Then system (4.6) is asymptotically stable if and only if for
Theorem 2. Suppose that conditions of Lemma 5 are satisfied. Let the matrix A of system (1.1) be in the form Then system (1.1) is asymptotically stable if and only if for
either
or
Proof. The proof is similar to Theorem 1.
5. An extension to a system of higher dimension
Finally, a higher dimensional linear delay differential system with two delays is considered
where is a real number,
is a
real constant matrix, and
,
are positive numbers such that
.
Theorem 3. Let be the eigenvalues of matrix A. Then system (5.1) is asymptotically stable iff
or
where ,
are real numbers and
.
Proof. Since be the eigenvalues of matrix A′ the characteristic equation of system (5.1) is given by
Thus, Theorem 3 can be seen as a result of Theorems 1 and 3.
Additional information
Funding
Notes on contributors
Serbun Ufuk Değer
My key research activities include Delay Differential Equations, Delay Difference Equations, Neutral Differential Equations, Neutral Difference Equations and stability of these equations. More generally, we can say Differential Equations, Difference Equations and stability of these equations.
The research reported in this paper relates to the stability of the systems that can be modeled by delay differential equations such as biology, physics and medicine. Thus, it is useful to use qualitative approaches to investigate the asymptotic stability of these systems. Our research represents a generalized method for describing the asymptotic stability of systems within of science branches such as biology and physics.
References
- Bellman, R., & Cooke, K. L. (1963). Differential-difference equations. New York, NY: Academic Press.
- Cooke, K. L., & Grossman, Z. (1982). Discrete delay, distributed delay and stability switches. Journal of Mathematical Analysis Applications, 86, 592–627. doi:10.1016/0022-247X(82)90243-8
- Cooke, K. L., & van den Driessche, P. (1986). On zeroes of some transcendental equations. Funkcialaj Ekvacioj, 29, 77–90. ( MR865215 (87m:34098))
- Elaydi, S. (2005). An introduction to difference equations (3rd ed.). New York, NY: Springer-Verlag.
- Freedman, H. I., & Kuang, Y. (1991). Stability switches in linear scalar neutral delay equation. Funkcialaj Ekvacioj, 34, 187–209.
- Gray, A., Greenhalgh, D., Hu, L., Mao, X., & Pan, J. A. (2011). Stochastic differential equation SIS epidemic model. SIAM Journal on Applied Mathematics, 71(3), 876–902. doi:10.1137/10081856X
- Hrabalova, J. (2013). Stability properties of a discretized neutral delay differential equation. Tatra Mountains Mathematical Publications, 54, 83–92.
- Ikeda, N., & Watanabe, S. (2014). Stochastic differential equations and diffusion processes (Vol. 24). North Holland: Elsevier.
- Insperger, T., & Stépán, G. (2011). Semi-discretization for time-delay systems: Stability and engineering applications (Vol. 178). New York, Dordrecht, Heidelberg, London: Springer Science & Business Media.
- Khokhlovaa, T., Kipnis, M., & Malygina, V. (2011). The stability cone for a delay differential matrix equation. Applied Mathematics Letters, 24, 742–745. doi:10.1016/j.aml.2010.12.020
- Kruthika, H. A., Mahindrakar, A. D., & Pasumarthy, R. (2017). Stability analysis of nonlinear time–delayed systems with application to biological models. International Journal of Applied Mathematics and Computer Science, 27(1), 91–103. doi:10.1515/amcs-2017-0007
- Kuang, Y. (1993). Delay differential equations with applications in population dynamics. MR1218880 (94f:34001) Boston: Academic Press.
- Li, Y., Ma, W., Xiao, L., & Yang, W. (2017). Global stability analysis of the equilibrium of an improved time-delayed dynamic model to describe the development of T Cells in the thymus. Filomat, 31(2), 347–361. doi:10.2298/FIL1702347L
- Liu, Q., Jiang, D., Shi, N., Hayat, T., & Alsaedi, A. (2016). Asymptotic behaviors of a stochastic delayed SIR epidemic model with nonlinear incidence. Communications in Nonlinear Science and Numerical Simulation, 40, 89–99. doi:10.1016/j.cnsns.2016.04.023
- Matsunaga, H. (2008). Delay dependent and delay independent stability criteria for a delay differential system. American Mathematical Society, 42, 4305–4312. ( 136 Fields Inst. Commun.)
- Nakajima, H. (2014). On the stability of a linear retarded differential-difference equation. Funkcialaj Ekvacioj, 57, 43–56. doi:10.1619/fesi.57.43
- Naresh, R., Tripathi, A., Tchuenche, J. M., & Sharma, D. (2009). Stability analysis of a time delayed SIR epidemic model with nonlinear incidence rate. Computers & Mathematics with Applications, 58(2), 348–359. doi:10.1016/j.camwa.2009.03.110
- Ruan, S., & Wei, J. (2003). on the zeros of transcendental functions with applications to stability of delay differential equations with two delays. Dynamic of Continuous, Discrete and Impulsive Systems, 10, 863–874.
- Smith, H. (2010). An introduction to delay differential equations with applications to the life science. New York, NY: Springer.
- Stepan, G. (1989). Retarded dynamical systems: Stability and characteristic functions, pitman research notes in mathematics series (Vol. 210). New York, NY: Academic Press.
- Stepan, G. (1998). Delay-differential equation models for machine tool chatter. Dynamics and Chaos in Manufacturing Processes, 471152935, 165–192.
- Xu, R. (2012). Global stability of a delayed epidemic model with latent period and vaccination strategy. Applied Mathematical Modelling, 36(11), 5293–5300. doi:10.1016/j.apm.2011.12.037