Abstract
We study a bilinear optimal control problem for an evolution equation with a nonlinear term that depends on both the state and its time integral. First, we establish existence and uniqueness results for this evolution equation. Then, we derive weak maximum principle results to improve the regularity of the state equation. We proceed by formulating an optimal control problem aimed at steering the system’s state to a desired final state. Finally, we demonstrate that this optimal control problem admits a solution and derive the first- and second-order optimality conditions.
Keywords:
differentiability; maximum principle; nonlocal-in-time; optimal control problem; parabolic partial differential equation; Schauder’s fixed-point theorem MSC:
35K58; 49K20; 90C46; 92D25
1. Introduction
We denote by a bounded open set of with a Lipschitz boundary . Also, let be an open subset of . For any , we set , and . Then, we turn our attention to the optimal control problem:
subject to the constraints that y solves the nonlinear and nonlocal-in-time parabolic
where
with and are given, and the set of admissible controls
with . The function , , and denote the characteristic function of the control set . We assume that there exists such that
and the function , and there exists such that
and
Equation (2) can be viewed as a model for population dynamics, where represents the population density at a specific location x and time t. The real function represents at any given time t and, at the location x, the aggregated history of a population’s density weighted by factors such as pathogen exposure, stress or other time-dependent influences. This dynamic approach allows a wide range of biological processes to be captured, including pathogen dynamics, resource competition and adaptive immunity or resistance. The real function models at any given time t and at the location x the mortality rate as a response to cumulative environmental, physiological or population-related factors. As a rate function, is positive and naturally bounded. We refer to [1], where the proof that can be lower bounded, i.e., is given. Mathematically, the assumption (6)–(7) on ensure the well-posedness of the system, the boundedness of solutions, and the characterization of the local optimal control.
In the literature, a system similar to (2), but with homogeneous Dirichlet boundary conditions and a second member for the state equation living in , has been studied. In [1], the author proved the existence and uniqueness of the weak solution and analyzed its asymptotic behavior. The establishment of the existence of a weak solution relies on the use of a fixed-point argument and Lebesgue’s dominated convergence theorem. For uniqueness, the standard approach of considering two solutions satisfying the same system and then proving that they are equal by using a subtraction technique that leads to a differential inequality, which forces the difference between the two solutions to be zero, has been applied. Another similar nonlocal-in-time parabolic problem, but with a different nonlinearity and homogeneous Dirichlet boundary conditions, has been studied in [2]. The nonlocal term involves an integral over the entire time interval, making the problem non-evolutionary in the traditional sense because the solution at any time depends on future values. The author proved the existence of a weak solution as well as its uniqueness. For the existence, the author built a weakly continuous map and applied Tikhonov’s fixed-point theorem. Using the standard method, the author proved the uniqueness of the solution under the conditions that the derivative of the nonlocal-in-time term is bounded, and the time interval T is sufficiently small. From the same author, Ref. [3] presents a similar system but with a slightly different nonlocal-in-time nonlinear term. The difference lies in the fact that the integral over the entire time interval is weighted. The author proved the existence of a weak solution without the use of any continuity properties of the solution in time. He has two existence results, one where the nonlinearity is a continuous bounded function and the other where the nonlinear term is a non-negative function that is not necessarily bounded. The demonstrations involve the use of estimates and weak convergences to show that a sequence of approximate solutions converges to a weak solution.
Optimal control of nonlinear partial differential Equations (PDEs) has been a subject of intensive works and applications in various fields. We refer, for instance, to [4,5,6,7,8,9,10,11] and the references therein. It is well established that the first-order optimality condition is both necessary and sufficient for studying optimal control problems associated with linear partial differential equations. However, in the case of nonlinear partial differential equations, the cost function is no longer convex. As a result, while the first-order optimality condition remains necessary, it is not sufficient. To address this, the second-order optimality condition is required, which involves analyzing the second derivative of the cost function with respect to the control. This ensures the local uniqueness of the optimal control. In this paper, we study an optimal control problem for a time-nonlocal parabolic equation. We start by establishing some regularity results for both the state equation and the cost function. Then, we prove that our optimal control problem as the local optimal solution that we characterize by means of the necessary and sufficient first-order and second-order optimality conditions.
The rest of this paper is organized as follows. Section 2 is devoted to the general framework and preliminary results. In Section 3, we establish a maximum principle and study the existence and uniqueness of a generalized nonlocal-in-time problem. Then, we deduce similar properties for system (2). In Section 4, we study the Lipschitz continuity and the differentiability of the solution to (2), then we prove existence of a local optimal control to problem (1) and characterize it using first- and second-order optimality conditions. Some concluding remarks are also given in Section 5.
2. General Framework and Preliminary Results
We give the general setting and some results that will be useful for the study of the control problem (1)–(2).
We recall that the Sobolev Space is defined as
Equipped with the norm
the space is a Hilbert space. We denote by the dual of . Next, we introduce the space
Endowed with the norm
the space is a Hilbert space. Furthermore, we have from ([12], Theorem 1.1, p. 102) that the following embedding is continuous:
Also, using ([13] Theorem 16.1, p. 110) and ([14], Theorem 5.1, p. 58), we obtain the following compact embedding:
The following results are essential for proving the existence of a solution to the nonlinear Equation (2), as well as the existence of a solution to the optimization problem discussed in Section 4.
Lemma 1.
Let the sequence be such that
for some constant independent of Then, there exists such that
Proof.
We then deduce from (11) that there exists such that
Hence, from the compact embedding (10), we obtain that
from which, thanks to the continuous embedding of into , we have that
□
From now on, we adopt the following notation for any appropriate function :
where and . We assume that there exists such that
Lemma 2.
Proof.
Lemma 3.
Proof.
Using (15) and the Cauchy–Schwarz inequality, we have that
from which we deduce (20). Proceeding exactly as above while using (16), we deduce (21).
From the linearity of the integral, (20) and (21), we can write
and
Passing to the limit when in these two inequalities while using (19), we obtain (22) and (23). To prove (24), we use the Lebesgue theorem. Indeed, in view of (22), we can extract a subsequence of still denoted such that
and since , we have that
Therefore, using (6) and (7), we have that there exists such that
Since Q is bounded domain, it follows from the Lebesgue dominated convergence theorem that
□
3. Analysis of the State Equation
In this section, we establish maximum principle and study the existence and uniqueness of a generalized nonlocal-in-time problem. Actually, the study of this auxiliary system allow us obtain similar properties for system (2) which also includes related systems such as its adjoint model. More precisely, we consider the following system:
where , , and . The functions , and . The function and are given by notation (15). We assume that (16) holds and that there exist and such that
and
Before going further, we give the definition of a weak solution to system (25).
Definition 1.
3.1. Maximum Principle
In this subsection, we will prove some estimates in the space . One necessary result is the one directly obtained from the Gagliardo–Niremberg Theorem (see, e.g., [15,16]) which we recall here.
Lemma 4.
Let . Then, , with . In addition, there exists a constant such that the following estimate
holds.
Another preliminary result in proving the maximum principle is the following theorem.
Theorem 1
([17], Lemma 4.1.1). We consider ρ a non-negative and non-increasing function on such that
where C, are positive constants with . Then, for all , where .
Theorem 2.
Proof.
First we need to make the following change for variable: where is a solution to (25) and . It follows that is a weak solution to
where in view of (15), and for a.e. .
Next, we introduce a real number such that . We easily deduce that for almost every , , and then we set which also resides in . Multiplying the first equation of system (25) by and then integrating by parts over , we obtain the following:
Hence,
Taking in this latter identity yields
and from (5), (6), (26), and (27) we obtain that for a.e. ,
Now, observing that and integrating (34) on , with and then using Cauchy–Schwarz’s inequality, we obtain that
and then choosing , we finally obtain
Hence,
and it follows from (36) that
Now, using Lemma 4, we obtain that
for some . Observing that
and using the Young’s inequality with and and then (39), we have that
Therefore, it follows from (37) and (38) that
We set . Then, is a measurable set. Moreover, we deduce from (41) that
Using Hölder’s inequality with and in the right hand side of (42), we obtain
from which we deduce that
where denotes the measure of the set .
Let , then . Consequently, for a.e. , we have and then, .
Thus,
Then, we obtain that
Hence,
Observing that for any , we have that . Hence, applying Theorem 1 with and , we deduce that where . Therefore, we have
We prove by setting and that the set , where , is a measure zero set. Consequently,
Now, since , we deduce that
□
From this Theorem based on the generalized model (25), we can derive similar properties for system (2).
Corollary 1.
Proof.
Proceeding as in Theorem 2 but with , , and , we easily prove that and that estimate (45) holds. □
In what following, we need the following result.
Lemma 5.
Let be sequence of . Assume that there exists and such that
and
Then, for any ,
Proof.
Since we can extract a subsequence of still denoted such that
Therefore, for any , we obtain that
and as there exists such that
Relation (46) follows from the Lebesgue’s dominated convergence theorem. □
3.2. Existence and Uniqueness Results
Theorem 3.
Let , , and . Also, let , , and be such that (5), (26), (16), (27), (6) and (7) hold. Then, there exists a unique weak solution to (25) in the sense of Definition 1.
Moreover, there exist and depending continuously on such that
and
Proof.
We proceed in three steps.
Step 1. We prove the existence results and estimations (48).
We use the Schauder’s fixed-point theorem. So, Let B be a non-empty, closed and convex subset of given by
where
Let . In view of Theorem A1, we have constructed the following nonlinear map
where . Here, is the weak solution to (A1):
Proving that has a fixed point will be enough to prove that (25) has a solution in . To this end, we use the Schauder’s fixed-point theorem.
Let . Since , where is the unique weak solution to (A1), using Corollary A1, we have that there exist and such that
and
From (51), we deduce that , and from (52), we have that is relatively compact in B because is relatively compact in . It remains to be proven that is continuous on B to obtain that a fixed point. So, let be a sequence of B such that
Let , the solution to (A1) with :
Then, from Corollary A1, we have that verifies
and there exist positive constants and such that
and
From (56), we have that there exists and a subsequence of still denoted by such that
and
Using Lemma 1 with , we deduce from (56) that
Thanks to Lemma 3, we have from (22) and (23) that
and
Applying Lemma 3 again, we have from (24) with that
From (6), (7) and Lemma 5, we obtain for any that
Passing to the limit in (54) when while using (5), (16), (27), (26), (57), (59), (61), (62), (63), and (64), we obtain that
Consequently, y is a weak solution to (A1). The uniqueness of the solution to (A1) allows us to conclude that converges strongly to in . This means that is continuous on B.
Step 2. We prove estimate (48)
If we set with where y is a solution to (25), we obtain that is a solution to
where in view of notation (15), and for a.e. .
Then, proceeding exactly as for the computation of (A11) and (A13), we prove that there there exist and such that
Step 3. We show the uniqueness of the solution.
Let be two solutions to (25) with the same source term f and initial value . If we set ) with , we obtain that is a solution to
where
If we multiply the first equation of (67) by z and integrate over Q, we obtain
which in view of (6) and the Mean Value Theorem implies that
Hence, thanks to Theorem 2, (20) and (21), we deduce that
where .
Choosing
from which we deduce that in Q. This means that □
Corollary 2.
Let and . Also, let and be such that (5), (6) and (7) hold. Then, there exists a unique weak solution to (2) provided that
holds for every .
Moreover, there exist positive constants and depending continuously on such that
and
Proof.
Lemma 6.
We now consider the system:
Proposition 1.
Proof.
If we make the change for variable in (73), we obtain that is a solution to
where , for almost every , . Since is a solution of (2), we have on the one hand that , and on the other hand, using (71) and (72), we have that and . Therefore, is a solution to (A1) with , , and . Thanks to Corollary A1 and Theorem 2, we deduce that there exists a unique weak solution to (76). Moreover, using (71) and (72), the continuous embedding of into , the continuous embedding of into , (A16) and (31) with , , , we have that there exists such that
Using (31), (71) and (72) again with , , , then (70), the embedding into , (71) and (72), we deduce that there exists such that
Since , we deduce (74) and (75). □
4. Resolution of an Optimal Control Problem
From Corollaries 1 and 2, we know that the weak solution y of system (2) resides in We introduce the following space:
and we observe that endowed with the graph norm
is a Banach space.
We also set the mapping given by
which is well defined, and the state equation as well as the initial data of system (2) can be viewed as
Moreover, taking into account the control-to-state mapping
we can rewrite the optimal control problem (1) as:
where
4.1. Sensitivity Analysis
Lemma 7.
Proof.
It is clear that the second component of is of class with respect to y and v. Since the first component of is also of class . Therefore, we can conclude that is of class . Moreover,
Let and . We consider the linear problem
Let and . Then, from (71), (72), and the system (81) is the same as (25) with , . Consequently, we have from Theorems 2 and 3 that there exists a unique which depends continuously on and on Since and satisfies (6) and (7), we have Therefore, . Hence, defines an isomorphism from to . Using the Implicit Function Theorem, we deduce that implicitly defines the control-to-state operator which is itself of class . □
Proposition 2.
Let . Under the assumptions of Lemma 7, the first derivative of the control-to-state operator is given by , where is the unique weak solution to
where according to (15) for almost every . The second derivative is given by , where is the unique weak solution to
where
and are respective solutions to (82) with and . Moreover, for every , the linear mapping can be extended to a linear continuous mapping on and there exists such that
and
Proof.
Let . We have from Lemma 7 that the control-to-state mapping is of class . Therefore, and exist. Using (6) and (7), we obtain after some computations that is a solution to (82) and is a solution to (83).
Applying Theorems 2 and 3 to solution to the system (82) with , , and , we deduce that . Moreover, using (31), (47), (48), (71) and (72), we obtain that there exists
such that
and
Proceeding as above, we also have that the solution to the system (82) with belongs to and satisfies the same estimation as . Since and belong to , we have from Lemma 2 that and belong also to . Consequently, using (6)–(7), the fact that the solution y to (2) belongs to , we obtain that defined in (84) belongs to . Therefore, applying Theorem 3 and Theorem 2 to solution to (83) with , , and we deduce that the problem (83) has also a unique weak solution □
Proposition 3.
Let and . Let and be such that (5), (6) and (7) hold. Also, let and be the unique weak solution to (2) and to (73), respectively. Then, the mappings and are Lipschitz continuous functions from onto . More precisely, for all , there is More precisely, for all , there is a constant and such that the following estimates hold
and
Proof.
Let and . Let where and are solutions of (2) with and respectively. Then, is a weak solution to
We multiply the first equation in (90) by p and intergate by parts over Q, which gives us
which in view of (6) and (45), we obtain that
Choosing in this
latter inequality, Since we deduce there exists such that (88) holds that
Next, let and . Let where and are solutions of (73) with and , respectively. Then, is a weak solution to
where
Using the linearity of the integral, the notation (5), (6), (7), (15), (20) of Lemma 3, the Cauchy–Schwarz inequality and the fact that , we have that
which in view of Young’s inequality implies that
If we multiply the first equation in (92) by z and integrate by parts over Q, we obtain
Choosing in this latter inequality and using (6) and (93), we deduce that
which in view of (45), (75), (88) and (91) implies that
for some .
Since , we have that
□
4.2. Optimization Problem
We introduce the following notion of local solutions.
Definition 2.
Theorem 4.
Proof.
Since for all we can have a minimizing sequence such that
From the structure of cost function J given by (3), there exists a constant independent of n such that
Since is the solution of (2) associated with the control , we know that satisfies
and in view of (70) in Corollary 2, there exists a constant independent of n such that
Using, on the one hand, the boundedness of in and (94), we have that there exist such that
and on the other hand, using (96) and Lemma 1, we deduce the existence of such that
and
Thanks to (22) and (101),
From (6) and Lemma 5, we have that for any ,
Passing to the limit in (95), while using the convergences (98), (100), (101) and (103), we obtain that
Thanks to Equation (68), is a weak solution of (2). In addition, since is a closed convex subset of , we have that
□
Proposition 4
(Twice Fréchet differentiability of J). Let be the solution of (2) and set where is given by (80). Then, following the hypothesis of Lemma 7, the functional is twice continuously Fréchet-differentiable, and for every , we have
and
where are solutions to (82) with and , respectively. is defined in (84), and is the unique weak solution to the adjoint Equation (73).
Proof.
From Lemma 7, we deduce that is twice continuously Fréchet-differentiable.
Let . After some computations, we obtain
If we multiply the first equation in (82) by such that on and integrate by parts over Q, we obtain
Hence, using the fact that , we have
Therefore, (108) can be rewritten as
So, if p verifies
where , then, in view of Proposition 1 and the uniqueness of solution to (73), . Hence, (109) becomes
Combining (107) and (110), we obtain (105).
Theorem 5.
Proof.
Let be arbitrary and v be an -local minimum. Since is convex, we have that for all Then, for all ,
which in view of (105) implies that
□
Lemma 8.
Proof.
Using the Cauchy–Schwarz inequality, (45) and (75), we have that
for some Thus, the mapping is linear and continuous on .
Since the cost functional given by (80) is non-convex, the first-order optimality conditions given in Theorem 5 are necessary but not sufficient for optimality. Sufficient second-order conditions are required. To this end, we first recall the definition of the feasible direction and the critical cone that can be found [18,19].
Definition 3.
- 1.
- The set of feasible directions is the set defined by
- 2.
- The critical cone is the set defined bywhere denotes the closure in of the admissible set .
Next, proceeding as in ([18] (Page 18)) (see also [19] (page 273)) we prove the following result that gives a characterization of the critical cone defined in (119).
Proposition 5.
Proceeding as in ([20] (p. 246)) or [21,22], we prove the following result.
Proposition 6
(Necessary second-order optimality conditions). Let be a -local solution of system (79). Then, , for all .
Theorem 6.
Let be a control satisfying the first-order optimality conditions (113). Then, the following hold:
- 1.
- The functional is of class . Furthermore, if we denote by and by the spaces of linear continuous functional on and bilinear continuous functional on then for every , the following continuous extensions exist:
- 2.
- For any sequence such thatas ,andIn addition, if , then
Proof.
We have that is a control satisfying the first-order optimality conditions (113). Thus, from Proposition 4 and Lemma 8, we have (122).
Step 1. We prove (125).
Let and the sequence be such that (123) and (124) hold. Then, we have that there exist and independent of n such that
If we denote by and , the solutions of (2) with and , respectively, and by and the solutions to (73) with and , respectively, then from (45), (70), (74) and (75), we have that and belong to . Moreover, from (45), (85), (75) and (87) we obtain
and
for some and . Using the Lipschitz continuity of the mapping and given in Proposition 3, we have that
and
Thanks to (130) and (132), we have that
On the other hand, in view of (129) and (130), the sequences are bounded in and thus in since Q is bounded. Therefore, we can prove using (129), (130), (131) and (132) that
Let and be the solutions to (82) with and , respectively. Then, and from (86) and (128), we have that there exist and independent of n such that
for some independent of n. Thanks to (20) of Lemma 3,
and
for some .
In addition, in view of (135), the compact embedding of into and the continuous embedding of into , we deduce that there exists such that
and
Thanks to (22) and (138) of Lemma 3,
Now, from (84) and (106),
Thus,
where we recall and as the solutions to (82) with and , respectively. Since satisfies (6) and (7), and the sequence satisfies (123) and (124), we have from (7), (129), (130), (135) and (136) that
and
where there exists Consequently, for any
and
which in view of the Cauchy—Schwarz inequality, (7), (129), (130) and (135) implies that
and
Thanks to (7), (24), (129), (130), (131), (132) and Lemma 5, for any ,
as . Therefore, passing to limit in (142) and in (143) while using the above convergence, (129), (130), (138) and (140), we deuce that
and
Thus
and
as Since is bounded in because (130) and (135),
Passing to the limi in this latter inequality while using (130), (133), (138) and the fact that , we deduce that
This means that
Then, using (141), (124), (144), (145), (138), (139) and (146), we obtain that
Finally, if , then , being the solution of (105), we have . Hence, passing to the lower limit in (141) when , we obtain (127). □
We have the following result giving sufficient second-order conditions for locally optimal solutions.
Theorem 7.
Let be a control satisfying the first-order optimality conditions (113) and
Then, there exist and such that the quadratic growth condition holds
Therefore, v is locally optimal in the sense of .
Proof.
Relation (148) is obtained by proceeding as ([19] Theorem 2.3, page 265) while using Proposition 6. □
5. Concluding Remarks
In this paper, we studied the optimal control of a nonlinear parabolic equation involving a nonlocal-in-time term. We proved some regularity results of systems and the existence of the optimal solution to our control problem. Since the system is nonlinear and thus the cost function non-convex, we obtain local uniqueness by means of the second optimality conditions.
Author Contributions
Conceptualization, G.M. and A.F.; methodology, G.M., A.F. and C.J.-A.; validation, G.M., A.F. and C.J.-A.; formal analysis, G.M.; investigation, A.F.; writing—original draft preparation, G.M.; writing—review and editing, G.M.; visualization, G.M., A.F. and C.J.-A.; supervision, G.M. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Data Availability Statement
Not applicable.
Conflicts of Interest
The authors declare no conflicts of interest.
Appendix A
For any , we consider the following system:
where , , and . The functions and are such that (5), (16), (26) and (27) hold. The functions and are defined as in (15).
Let . If we make the change for variable , where y is a solution of (A1), then p satisfies:
where in view of notation (15), and for a.e. .
Definition A1.
Theorem A1.
Proof.
We proceed in four steps.
Step 1. We prove that there exists the solution to (A2).
We recall that the norm on is given by:
and we define the norm on by:
Then, we have the continuous embedding .
Let be the bilinear functional given for all by:
Using Cauchy–Schwarz’s inequality, (5), (6), (16), (26) and (27), we obtain that
where is given by
Consequently, for every fixed the functional is continuous on
For every ,
In view of (5), (16), (26) and (27), we have for any ,
Hence, using (6) and the definition of the norm on given by (A6), we obtain that
Choosing in this latter inequality , we
obtain that
Thus
is coercive on
Finally, we consider the functional defined by
Using Cauchy–Schwarz’s inequality,
which in view of the definition of he norm on given by (A6) implies that is continuous on . Since we have proved that the bilinear functional is coercive on and continuous on , for every fixed Theorem 1.1 ([23] Page 37) allows us to say that there exists such that .
Step 2. We show that .
Since , using (6) and the fact that , and , we have that for almost every
If we take the duality map between the first equation in (A2) and we obtain
which in view of (5), (6), (16), (26), (27) and the Cauchy–Schwarz inequality implies that
Observing that we have that
for some .
Hence, using (5), (6), (16), (27), (26) and the Young’s inequality, we deduce that
which, because gives
Hence, (A8) becomes
From (A10), (A11) and the definition of the norm on given by (8), we deduce that
where depends continuously on .
Step 4. We prove the uniqueness of p solution to (A2).
Assume that there exist and solutions to (A2) with the same right hand side f and initial value . Let . Then, q is a solution to (A2) with and :
Multiplying the first equation in (A12) by q, integrating by parts over , then using (A9), with , and , we obtain that
which, because gives
This implies that in Q and therefore in Q. □
The following results for system (A1) follow from Theorem A1 and the change of variable , with .
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