1. Introduction
Pang and Stewart [
1] pioneered differential variational inequality in the context of engineering challenges, capturing the mathematical literature. The differential variational inequality is a strong tool for studying numerous models, such as ideal diode electrical circuits, contact of deformable bodies, traffic networks and hybrid engineering systems with changing topologies. In [
2], the topological degree theory was used to examine the periodic solution of a differential variational inequality, and in the study of two parameters, periodic solutions for a class of differential variational inequalities. Significant results in the field are contained in [
3,
4,
5,
6,
7,
8].
A differential variational inequality is a system that combines a variational inequality with an evolution equation and concludes the attributes of the solution set that are derived through the suitable conditions of compactness, convexity and set of constraints. In [
9], further results were gained by relaxing the set’s compactness. The existence results for differential variational inequalities involving non-compact sets of constraints and non-local boundary conditions are given in the citation [
10,
11,
12].
The penalty techniques are a type of mathematical instrument that can be used to solve a wide range of issues, including constrained problem analysis and numerical solutions. The purpose of penalty techniques is to create a sequence of unconstrained problems that converge to the solution as the penalty parameter approaches zero. Many authors have looked into penalty approaches for variational inequalities, primarily for numerical purposes; see [
13,
14,
15] and the references therein for more information. However, the majority of references only employ penalty techniques to analyze a variational inequality, and few studies deal with penalty methods for differential variational inequalities. The authors demonstrate that a penalty approach to analyzing differential variational inequalities yields existence, uniqueness and convergence results; see [
16,
17,
18,
19,
20].
The goal of this paper is to suggest a penalty method for differential variational inequality problems in Banach spaces. We construct a sequence of problems by utilizing the set of constraints, symmetry and penalty parameters and prove the convergence of sequences to the solution of the problem in the sense of Mosco. Finally, we discuss the boundary value problem for the differential variational inequality problem with unilateral constraints.
2. Preliminaries
Throughout this paper, we denote by and the reflexible Banach spaces. Let be the space of linear continuous operators on endowed with the norm . In addition, we denote by the dual of , by the zero element of and by the duality pairing between and . Furthermore, we use for the product of the spaces and with the canonical product topology. Moreover, for , we denote by the space of continuous functions defined on with values in , and we use for the set of continuous functions defined on with values in . Even if we do not explicitly state it, all limits, lower limits and upper limits are assumed to be . We need to recall the following definitions.
Definition 1 ([
21,
22])
. Let be the function. Then is said to be- (i)
- (ii)
strongly monotone, if there exists such that - (iii)
inverse strong monotone, if there exists such that - (iv)
Lipschitz continuous, if there exists such that - (v)
bounded, if there are maps bounded sets in into bounded sets of
- (vi)
pseudomonotone, if is bounded and for every sequence converging weakly to such that - (vii)
hemicontinuous, if for all , the function is continuous on ;
- (vii)
demicontinuous, if implies
Definition 2. An operator is said to be a penalty operator of the set if is bounded, demicontinuous, monotone and Definition 3. Let be the function. The φ is said to be lower semicontinuous, ifand for any sequence , Definition 4. Let be a sequence of non-empty subsets of and let . If the sequencethen the following holds: - (i)
For each , there exists a sequence such that for , and - (ii)
For each sequence such that for , and , we have
We shall denote the Mosco convergence by
which is proposed in [
23].
Assume that
and
and
. In addition, let
,
and
. From now on we note that
and
unless otherwise specified. With these data, we consider the following differential variational inequality problem for finding two functions
and
such that
where
is a derivative of
x with respect to the time variable
and the inclusion
is a notation which means that
satisfies the variational inequality problem
We evaluate the following assumptions on the data in the research of (
1).
Therefore, we recall that
Definition 5 ([
24,
25])
. A pair of functions is said to be a solution of (
1)
if , andAssume that if is a solution of (
1),
then x is called the mild trajectory and u is the variational control trajectory. We are now able to establish the following existence and uniqueness results.
Theorem 1. Assume that (
3), (
8)
are satisfied. Then there exists a unique solution to (
1).
Proof. Theorem 1 was demonstrated in [
16] under the following additional assumption: either
is a bounded subset in
or there exists an element
such that
However, if
is unbounded, then conditions (
6)(a) and (
7) guarantee the legitimacy of (
10) with any
.
Let
and
be fixed. We compose
By inverse strong monotonicity and Lipschitz continuity of
, we obtain
We know that
is convex and lower semicontinuous, and there exists an element
and a constant
such that
see ([
26], Proposition 5.2.25). Hence, from (
11) and (
12), we infer that
Therefore, (
13) shows that when
is unbounded, we have
As a result, condition (
10) is true for any
, as claimed. To finish the proof, we will employ ([
16], Theorem 3.1). □
3. Main Results
In this section, we suggest the penalty approach for (
1). It entails identifying that the approximation problem has a unique solution, and the sequence of the problem converges to the unique solution of (
1). To that end, we consider an operator
, two sequences
, and for each
the differential variational inequality problem for finding a pair of functions
with
and
such that
where
is a notation and
is satisfying the variational inequality problem:
We evaluate the following hypotheses on the data in the research of (
14).
We recall from Definition 5 that the functions
are a solution of (
14); if
,
, then
and
The following are our main results in this paper.
Theorem 2. Assume that (
3), (
4), (
6), (
8), (
16)
and (
18)
are satisfied. Then for : - (1)
There exists a unique solution of (
14).
- (2)
If (
5), (
19)
and (
20)
hold as well, then the functions of (
14)
converge to the unique solution of (
1)
obtained in Theorem 1, i.e., for all
Proof. - (1)
For
, the function
is defined by
Under the hypotheses (
6), (
17) and (
18), it is simple to see that
meets condition (
6) with the constants
and
. As a result, since (
16) holds, we can utilize the Theorem 1 with
. Hence, the first part of the proof concludes with the deduction that there exists a unique solution
to the system (
14).
- (2)
In the second part, we suppose that (
5) and (
19)–(
20) are satisfied. For
, the auxiliary problem for finding a function
is:
Take note of the fact that
x is the mild trajectory of (
1). We utilize a standard result on time-dependent variational inequalities to see that the problem (
23) has a unique solution
The rest of the proof is now divided into four steps.
- Step (i)
Assert that for
, there exists a subsequence of the sequence
, again denoted by
which converges weakly to
in other words,
To prove this assertion, we fix
and
. Using the inverse strong monotonicity and Lipschitz continuity of
q, (
23) with
and (
19)(c), we obtain
Now, from (
12), we have
where
Now we use the inequality
to obtain
According to the above inequality, we see that the sequence
is bounded in
. Thus, the sequence
is also bounded in
. Since
is a reflexive Banach space, there exists
such that, passing to a subsequence if necessary, denoted by
is weakly convergent. Therefore, from assumption (
6)(b) and Definition 4(ii),
implies that
and the statement is proved.
- Step (ii)
For all
, we claim that
According to Definition 4(i), let
and
, then there exists a sequence
such that
and
From (
6) and (
7), we combine the functions
q,
with the convergence of
and boundedness
to show that there exists a positive constant
which does not depend on
n, such that
Since the sequence
converges in
and the sequence
is bounded in
, we have
Furthermore, the regularity
allows us to take
in (
26) to obtain
However, keep in mind that assumption (
18) ensures the operator
is bounded, demicontinuous and monotone. From [[
27], Theorem 3.69], we can derive that
is pseudomonotone. Thus, the pseudomonotonicity of
together with (
27) is taken to imply
The Equations (
16) and (
19)(a) ensure that
, and from (
28) derive that
Now adding the inequality (
29) with assumption (
19)(c), we find that
Then from assumption (
19)(d), we obtain the regularity
Assume that
. Then from the inequality (
23), we obtain
Therefore, from assumption (
19)(c) we have
Again, from the monotonicity of
q we have
and from (
31), we find that
Using the upper limit of the inequality, the assumption (
7) and the convergence (
24), we obtain
For
and
, we take
. Then, from (
30) and (
5), we have
Hence, with the convexity
together with the previous inequality, we have
Taking
and (
6)(a), we obtain
We point out that the assumption (
6)(a) ensures that the solution of this inequality is unique. Hence, from the uniqueness,
is a unique solution of the above inequality. Therefore, we derive that
and our claim is proved.
- Step (iii)
For , we show that
Let . To begin a careful observation of the proofs in steps (i) and (ii) shows that any weakly convergent subsequence of the sequence converges weakly to in as . Furthermore, the sequence is bounded and the whole sequence weakly converges to in .
Taking
in (
31) and going to the upper limit, we can observe that
Taking the inequality (
33) together with (
24) and the pseudomonotonicity of the function
q, ensured by assumption (
6)(a), we have
We put
in the above inequality to obtain
Using now inequalities the (
33) and (
34), it follows that
Using the inverse strong monotonicity and Lipschitz continuity of
q together with
and (
35), we have
The proof of Step (iii) is completed.
- Step (iv)
Eventually, we prove
where
is a unique solution of (
1).
For
,
and
, we have
Put
in (
36) and
in (
36), and adding these inequalities with the monotonicity of
, we obtain
Combining the above inequality with (
6) leads to
On the other hand, when we use (
9) and (
21), we obtain
where
is a positive constant, such that
From (
4) and (
37), we obtain
From the Gronwall inequality, there exists a positive constant
(does not depend on
n), so we have
This inequality combined with the
the boundedness result in the proof of Step (i) and the Lebesgue convergence theorem implies that
Again, we use inequality (
37),
obtained in Step (iii) and (
38) to show that
Therefore, we say that the convergence (
22) is a direct consequence of (
38) and (
39), and the proof is completed.
□
Now, we discuss the special cases of Theorem 3.1. To this end, we assume that (
3), (
8) hold and
is a solution of (
1) provided by Theorem 1. Ensure that this solution satisfies
Assuming that and do not depend on n, then we have the following corollary of Theorem 2.
Corollary 1. Assume that (
3), (
8), (
17), (
18), (
20)
hold, and assume that there exists a convex closed subset of such that and (
19)
(c), (d) hold. For each , there exists a unique pair of functions such that Moreover, the convergence (
22)
holds, for any . Remark 1. - (i)
If , then Corollary 1 represents the main convergence result studied in [16] and inequality (
42)
is an unconstrained variational inequality. - (ii)
If set is different from the whole space , then inequality (
42)
may be a time-dependent variational inequality with constraints. - (iii)
In general, case Corollary 1 will be the solution of the differential variational inequality (
42), (
43)
governed by the set of constraints Ω
and can be approached by the solution of the differential variational inequality (
42), (
43)
governed by a different set of constraints as the penalty parameter is small enough.
4. Parabolic–Elliptic Equations
Suppose that ℧ is a bounded domain of
with a smooth boundary
ℸ, separated in two measurable portions
and
, such that
Assume that
is a finite interval of time. The spatial variable denoted by
and the time variable by
, and the
is the outward unit normal at
ℸ. We investigate the following parabolic–elliptic problem with these notations for finding
and
such that
We utilize the Lebesgue and Sobolev spaces to study the problem (
44)–(
49). Furthermore, we define the space
with the inner product
and norm
Let
be a Hilbert space.
is used for the dual of
and
is used for the duality pairing mapping between
and
Now, we consider the following assumptions about the data.
Now, we assume that the functions
,
,
,
and
are defined by
Using the above notation, we can conclude the following variational formulation of problems for finding
and
, such that
Theorem 3. Assume (
52), (
57)
holds true. Then the problem (
63)–(
65)
has a unique solution Proof. The proof of Theorem 3 may be found by applying the Theorem 1 with
,
defined in (
50) and (
51) and
,
p,
q,
g,
,
given in (
58), (
62). It is simple to verify that the conditions (
3), (
21) are met in this scenario. We omit the details of the proof that are identical to those in [
16]. □
For
, we investigate the boundary value problem for finding
and
that satisfies (
44), (
46), (
48), (
49) and
Now we revel in the problem (
14) to replace the condition (
47) with the condition (
66). There,
,
and
is a function that has the following properties:
The example of a such function is given by
where
and
is a negative part of
r, i.e.,
Again, we define the sets
,
and
by
Then, the variational formulation of (
66) is a problem for finding
and
, such that
The following is the critical feature of this section.
Theorem 4. Assume that (
52), (
57), (
67), (
69), (
17)
and (
20)
hold. Then for , there exists a unique solution to (
73)–(
75).
Furthermore, the solution converges to of (
66)
obtained in Theorem 3, i.e., for all Proof. We use Theorem 2 on the spaces
and
suggested in (
50), with (
58), (
62), (
70) and (
72). To begin, we should observe that assumption (
67) implies that condition (
16) and (
19)(a) are satisfied. Second, it is straightforward to demonstrate that the operator (
72) meets condition (
18) using the attributes (
67) of the function
h. Using the assumption (
68), we may derive that
implies that (
19)(b) holds as well.
Next, suppose that
and
. Then from (
67), we have
which implies
Therefore,
and (
19)(c) holds. Next, from
and
which argues that
Therefore, the connotation
together with (
77) and (
79) give
Combining the above equality with assumption (
67)(d) leads to
Eventually, we see that
and the condition (
19)(d) holds.
Now, the assumptions (
17) and (
20) are true. Furthermore, the proof of Theorem 3 establishes the validity of the remaining criteria in Theorem 2. We can now employ Theorem 2 in the investigation of (
1) and (
14) to finish the proof. □
5. Conclusions
Differential variational inequality problems can be viewed as natural and innovative generalizations of differential variational inclusion problems. Two of the most difficult and important problems related to these inequalities are the establishment of the sequences of the problem with a set of constraints and a penalty parameter. In this article, a differential variational inequality problem is suggested and studied, which is more general than many existing problems in the literature. The discussion of differential variational inequality problem depends on the concepts of compactness, symmetry, pseudomonotonicity, Mosco convergence, inverse strong monotonicity and Lipschitz continuous mapping. Finally a parabolic–elliptic equation of the initial and boundary values problem is also discussed as an illustration.
Author Contributions
Methodology, S.-S.C.; investigation, S.; visualization, L.W.; software, Z.M. All authors have read and agreed to the published version of the manuscript.
Funding
This work was supported by the Natural Science Foundation of China (Grant 12161088). This work was also supported by the Natural Science Foundation of China Medical University, Taichung, Taiwan.
Data Availability Statement
The data sets used and/or analysed during the current study are available from the corresponding author on reasonable request.
Acknowledgments
The authors are grateful to the anonymous referee for their useful comments and suggestions, which have improved the quality of the paper.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Pang, J.S.; Stewart, D.E. Differential variational inequalities. Math. Program. 2008, 113, 345–424. [Google Scholar] [CrossRef] [Green Version]
- Liu, Z.H.; Loi, N.V.; Obukhovskii, V. Existence and global bifurcation of periodic solutions to a class of differential variational inequalities. Int. J. Bifurc. Chaos 2013, 23, 1350125. [Google Scholar] [CrossRef]
- Loi, N.V. On two-parameter global bifurcation of periodic solutions to a class of differential variational inequalities. Nonlinear Anal. 2015, 122, 83–99. [Google Scholar] [CrossRef]
- Chang, S.S.; Salahuddin; Wang, L.; Liu, M. On the weak convergence for solving semistrictly quasi-monotone variational inequality problems. J. Inequal. Appl. 2019, 74, 74. [Google Scholar] [CrossRef]
- Kinderlehrer, D.; Stampacchia, G. An Introduction to Variational Inequalities and Their Applications. In Classics in Applied Mathematics; SIAM: Philadelphia, PA, USA, 2000; Volume 31. [Google Scholar]
- Ke, T.D.; Loi, N.V.; Obukhovskii, V. Decay solutions for a class of fractional differential variational inequalities. Fract. Calc. Appl. Anal. 2015, 18, 531–553. [Google Scholar]
- Lu, L.; Liu, Z.H.; Obukhovskii, V. Second order differential variational inequalities involving anti-periodic boundary value conditions. J. Math. Anal. Appl. 2019, 473, 846–865. [Google Scholar] [CrossRef]
- Melanz, D.; Jayakumar, P.; Negrut, D. Experimental validation of a differential variational inequality-based approach for handling friction and contact in vehicle/granular-terrain interactio. J. Terramech. 2016, 65, 1–13. [Google Scholar] [CrossRef] [Green Version]
- Liu, Z.H.; Zeng, S.D. Differential variational inequalities in infinite dimensional Banach spaces. Acta Math. Sci. 2017, 37, 26–32. [Google Scholar] [CrossRef]
- Liu, Z.H.; Migórski, S.; Zeng, S.D. Partial differential variational inequalities involving nonlocal boundary conditions in Banach spaces. J. Differ. Equ. 2017, 263, 3989–4006. [Google Scholar] [CrossRef]
- Lu, L.; Liu, Z.H.; Motreanu, D. Existence results of semilinear differential variational inequalities without compactness. Optimization 2019, 68, 1017–1035. [Google Scholar] [CrossRef]
- Li, L.; Lu, L.; Sofonea, M. Generalized penalty method for semilinear differential variational inequalities. Appl. Anal. 2022, 101, 437–453. [Google Scholar] [CrossRef]
- Migórski, S.; Zeng, S.D. Penalty and regularization method for variational hemivariational inequalities with application to frictional contact. Z. Angew. Math. Mech. 2018, 98, 1503–1520. [Google Scholar] [CrossRef]
- Sofonea, M.; Migórski, S.S.; Han, W. A penalty method for history-dependent variational-hemivariational inequalities. Comput. Math. Appl. 2018, 75, 2561–2573. [Google Scholar] [CrossRef]
- Glowinski, R. Numerical Methods for Nonlinear Variational Problems; Springer: New York, NY, USA, 1984. [Google Scholar]
- Liu, Z.H.; Zeng, S.D. Penalty method for a class of differential variational inequalities. Appl. Anal. 2019, 19, 1574–1589. [Google Scholar] [CrossRef]
- Migórski, S.; Liu, Z.H.; Zeng, S.D. A class of history-dependent differential variational inequalities with application to contact problems. Optimization 2020, 69, 743–775. [Google Scholar] [CrossRef]
- Chang, S.S.; Salahuddin; Wang, L.; Wang, G.; Zhao, Y.H. Existence and convergence results for generalized mixed quasi-variationa Hemivariational inequality problem. Symmetry 2021, 13, 1882. [Google Scholar] [CrossRef]
- Chang, S.S.; Ahmadini, A.A.H.; Salahuddin; Liu, M.; Tang, J.F. The optimal control problems for generalized elliptic Quasivariational inequalities. Symmetry 2022, 14, 199. [Google Scholar] [CrossRef]
- Salahuddin. On penalty method for non-stationary general set valued equilibrium problems. Commun. Appl. Nonlinear Anal. 2016, 23, 82–92. [Google Scholar]
- Kim, J.K.; Salahuddin; Lim, W.H. General nonconvex split variational inequality problems. Korean J. Math. 2017, 25, 469–481. [Google Scholar]
- Kim, J.K.; Dar, A.H.; Salahuddin. Existence solution for the generalized relaxed pseudomonotone variational inequalities. Nonlinear Funct. Anal. Appl. 2020, 25, 25–34. [Google Scholar]
- Mosco, U. Convergence of convex sets and of solutions of variational inequalities. Adv. Math. 1969, 3, 510–585. [Google Scholar] [CrossRef] [Green Version]
- Liu, Z.H.; Zeng, S.D.; Motreanu, D. Evolutionary problems driven by variational inequalities. J. Differ. Equ. 2016, 260, 6787–6799. [Google Scholar] [CrossRef]
- Pazy, A. Semigroups of Linear Operators and Applications to Partial Differential Equations; Springer: New York, NY, USA, 1983. [Google Scholar]
- Denkowski, Z.; Migórski, S.; Papageorgiou, N.S. An Introduction to Nonlinear Analysis: Theory; Kluwer Academic/Plenum Publishers: Dordrecht, The Netherlands, 2003. [Google Scholar]
- Migórski, S.; Ochal, A.; Sofonea, M. Nonlinear inclusions and hemivariational inequalities. In Models and Analysis of Contact Problems; Springer: New York, NY, USA, 2013. [Google Scholar]
| Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).