- Research
- Open Access
- Published:
A posteriori error estimates for fourth order hyperbolic control problems by mixed finite element methods
Boundary Value Problems volume 2019, Article number: 90 (2019)
Abstract
In this paper, we consider the a posteriori error estimates of the mixed finite element method for the optimal control problems governed by fourth order hyperbolic equations. The state is discretized by the order k Raviart–Thomas mixed elements and control is discretized by piecewise polynomials of degree k. We adopt the mixed elliptic reconstruction to derive the a posteriori error estimates for both the state and the control approximations.
1 Introduction
The finite element approximation for optimal control problems has an enormously important function in the numerical approach for these problems. Scientists have studied extensively this area; see, for example, [4, 12, 13, 21, 25]. They discussed the a priori error estimates using finite element approximations, such as [1, 16, 23], in which elliptic or parabolic problems are considered by optimal control theory. They studied adaptivity for many optimal control problems; for example, see [4, 11, 17, 20,21,22].
In some optimal control problems, for the objective function containing a gradient of the state variable, we use mixed finite element methods to discretize the state equation, so that the scalar variable and its flux variable can be approximated in the same accuracy; for example, see [3]. Many scientists have addressed the mixed finite element methods for elliptic problems [6,7,8, 14], for the first bi-harmonic equation [5], for parabolic problems [26] and for hyperbolic problems [9, 15].
The purpose of this work is to discuss the a posteriori error estimates of the semidiscrete mixed finite element approximation for fourth order hyperbolic optimal control problems. Considering the fourth order hyperbolic equations by the idea of a mixed elliptic reconstruction [24], we obtain the error estimates for the state and the control approximations. The following is the model we considered:
where \(\varOmega \subset {\mathbf{R}^{2}}\) is an open set of polygon with ∂Ω. K is in \(U=L^{2}(J;L^{2}(\varOmega ))\), a closed convex set, \(J=[0,T]\), \(f,y_{d}\in L^{2}(J;L^{2}(\varOmega ))\) and \(y_{0}, y_{1}\in H^{4}(\varOmega )\). K is defined as follows:
Let \(\tilde{y}=-\Delta y\), \(\tilde{\boldsymbol{p}}=-\nabla y\) and \(\boldsymbol{p}=- \nabla \tilde{y}\), then (1.1)–(1.5) can be written as
In the paper, we adopt the standard notation \(W^{m,p}(\varOmega )\) for Sobolev space on Ω with a norm \(\Vert v\Vert _{m,p}\) given by \(\Vert v \Vert _{m,p}^{p}:=\sum_{\vert \alpha \vert \leq m}\Vert D^{\alpha }v\Vert _{L^{p}(\varOmega )}^{p}\), and a seminorm \(\vert v\vert _{m,p}\) given by \(\vert v\vert _{m,p}^{p}:=\sum_{\vert \alpha \vert = m}\Vert D^{\alpha }v\Vert _{L^{p}( \varOmega )}^{p}\). We set \(W_{0}^{m,p}(\varOmega )=\{v\in W^{m,p}(\varOmega ): \gamma (D^{\alpha }v )\vert _{\partial \varOmega }=0, \vert \alpha \vert =m \}\), where γ is the trace operator. We denote \(W^{m,2}(\varOmega )(W_{0}^{m,2}(\varOmega ))\) by \(H^{m}(\varOmega )(H_{0}^{m}(\varOmega ))\).
We denote by \(L^{s}(0,T;W^{m,p}(\varOmega ))\) the Banach space of all \(L^{s}\) integrable functions from J into \(W^{m,p}(\varOmega )\) with norm \(\Vert v\Vert _{L^{s}(J;W^{m,p}(\varOmega ))}= (\int _{0}^{T}\Vert v\Vert _{W^{m,p}( \varOmega )}^{s}\,dt )^{\frac{1}{s}}\) for \(s\in [1,\infty )\), and the standard modification for \(s=\infty \). For simplicity of presentation, we denote \(\Vert v\Vert _{L^{s}(J;W^{m,p}(\varOmega ))}\) by \(\Vert v\Vert _{L^{s}(W^{m,p})}\). Similarly, one can define the spaces \(H^{1}(J;W^{m,p}(\varOmega ))\) and \(C^{k}(J;W^{m,p}(\varOmega ))\). We can find details in [19]. C is a general positive constant independent of h.
The rest of this paper is as follows: In Sect. 2, we introduce the optimal control problems and its mixed finite element scheme. Section 2 ends with the definition of the mixed elliptic reconstructions, which is useful in deriving the a posteriori estimates for the fourth order hyperbolic optimal control problems in Sect. 3. Finally, we make some concluding remarks in Sect. 4.
2 Optimal control problems for mixed methods
A semidiscrete approximation of a mixed finite element for the optimal control problems (1.7)–(1.14) will be constructed. We set the state spaces \(\boldsymbol{L}=L^{2}(J;\boldsymbol{V})\), \(\boldsymbol{L}_{0}=L^{2}(J;\boldsymbol{V}_{0})\) and \(Q=L^{2}(J;W)\), \(W=L^{2}(\varOmega )\), where V, and \(\boldsymbol{V}_{0}\) are defined as follows:
The space V is a Hilbert space, its norm is defined as follows:
Now we introduce operators: div, ∇, curl and Curl. For any \(\boldsymbol{v}=(\boldsymbol{v}_{1},\boldsymbol{v}_{2})\in (H ^{1}(\varOmega ))^{2}\) or \(w\in H^{1}(\varOmega )\),
Next, (1.7)–(1.14) can be rewritten into weak form as follows: find \((\tilde{\boldsymbol{p}},y,\boldsymbol{p},y,u)\in (\boldsymbol{L}_{0}\times Q\times \boldsymbol{L}\times Q\times K)\), such that
From [18], we know that the above optimal control problem has a unique solution \((\tilde{\boldsymbol{p}},y,\boldsymbol{p},\tilde{y},u)\), and that \((\tilde{\boldsymbol{p}},y,\boldsymbol{p},\tilde{y},u)\) is the solution of (2.3)–(2.9) if and only if there is a co-state \((\tilde{\boldsymbol{q}},z,\boldsymbol{q},\tilde{z})\in (\boldsymbol{L}_{0}\times Q\times \boldsymbol{L}\times Q)\) such that \((\tilde{\boldsymbol{p}},y,\boldsymbol{p},\tilde{y}, \tilde{\boldsymbol{q}},z,\boldsymbol{q},\tilde{z},u)\) satisfies the following optimality conditions:
where \((\cdot ,\cdot )\) is the inner product of \(L^{2}(\varOmega )\).
K is a control constraint, so we can get a relationship between u and z. This relationship is important for our result.
Lemma 2.1
Let \((z,u)\) be the solution of (2.10)–(2.22). Then we have \(u=\max\{0,{\check{z}}\}-z\), where
denotes the integral average on \(\varOmega \times J\) of the function z.
Let \({\mathcal{T}}_{h}\) be regular triangulations of Ω, \(h_{\tau }\) is the diameter of τ and \(h=\max h_{\tau }\). Furthermore, let \(\mathcal{E}_{h}\) be the set of element sides of the triangulation \({\mathcal{T}}_{h}\) with \(\varGamma _{h}=\bigcup \mathcal{E} _{h}\). Let \(\boldsymbol{V}_{h}\times W_{h}\subset \boldsymbol{V}\times W\) denote the Raviart–Thomas space [3] associated with the triangulations \(\mathcal {T}_{h}\) of Ω. \(P_{k}\) denotes the space of polynomials of total degree no greater than k (\(k\geq 0\)). Let \(\boldsymbol{V}({\tau })= \{\boldsymbol{v}\in P_{k}^{2}({\tau })+x\cdot P_{k}({\tau })\}\), \(W({\tau })=P _{k}({\tau })\). We set
We now discretize (2.3)–(2.9). We calculate \(( \tilde{\boldsymbol{p}}_{h},y_{h},\boldsymbol{p}_{h},\tilde{y}_{h},u_{h})\) such that
where \(y_{0}^{h}(x)\in W_{h}\) and \(y_{1}^{h}(x)\in W_{h}\) are the mixed elliptic projections of \(y_{0}\) and \(y_{1}\). The optimal control problem (2.23)–(2.29) again has an unique solution \(( \tilde{\boldsymbol{p}}_{h},y_{h},\boldsymbol{p}_{h},\tilde{y}_{h},u_{h})\), and \((\tilde{\boldsymbol{p}}_{h},y_{h},\boldsymbol{p}_{h},\tilde{y}_{h},u_{h})\) is the solution of (2.23)–(2.29) if and only if there is a co-state \((\tilde{\boldsymbol{q}}_{h},z_{h},\boldsymbol{q}_{h},\tilde{z}_{h})\) such that the following optimality conditions hold:
For Lemma 2.1, the relationship between \(u_{h}\) and \(z_{h}\) is given as follows:
where \({\check{z}_{h}}=\frac{\int _{0}^{T}\int _{\varOmega }z_{h}\,dx\,dt}{\int _{0}^{T}\int _{\varOmega }1\,dx\,dt}\) is the integral average on \(\varOmega \times J\) of the function \(z_{h}\).
Now, we give the local definition of \(\operatorname {div}_{h}\), \(\operatorname{curl} _{h}:H^{1}(\mathcal {T}_{h})^{2}\rightarrow L^{2}(\varOmega )\) and \(\nabla _{h}\), \(\operatorname{Curl}_{h}:H^{1}(\mathcal {T}_{h})\rightarrow L^{2}(\varOmega )^{2}\), such that for any \(T\in \mathcal {T}_{h}\)
Set \(P_{h}:W\rightarrow W_{h}\) to be the orthogonal \(L^{2}(\varOmega )\)-projection into \(W_{h}\) [2], which satisfies
Next, introduce the Fortin projection (see [3] and [10]) \(\varPi _{h}: \boldsymbol{V}\rightarrow \boldsymbol{V}_{h}\), which satisfies: for any \(\boldsymbol{q}\in \boldsymbol{V}\)
The commuting diagram property reads
where I denotes the identity operator.
Next, the intermediate variable \(\tilde{u}\in K\) is introduced as follows:
Next, we present mixed elliptic constructions \((\tilde{\bar{\boldsymbol{p}}}, \bar{y}, \bar{\boldsymbol{p}}, \tilde{\bar{y}},\tilde{\bar{\boldsymbol{q}}}, \bar{z},\bar{\boldsymbol{q}}, \tilde{\bar{z}})\in (\boldsymbol{V}\times W)^{4}\):
For simplicity of presentation, we resolve the errors in following forms:
From mixed elliptic reconstructions [24], we derive the error estimates as below.
Lemma 2.2
For Raviart–Thomas elements, there exists a positive constant C which depends the domain Ω, the shape regularity of the elements and polynomial degree k such that
where \(\nabla _{h}\) and \(\operatorname{curl}_{h}\) have been defined in (2.44)–(2.45), \(J(\boldsymbol{v}\cdot \boldsymbol{t})\) denotes the jump of \(\boldsymbol{v}\cdot \boldsymbol{t}\) across the element edge E for all \(\boldsymbol{v}\in \boldsymbol{V}\) with t being the tangential unit vector along the edge \(E\in \varGamma _{h}\).
3 Error estimation of optimal control
In this part, a posteriori error estimation of optimal control problems shall be given. From (2.53)–(2.56) and (2.65)–(2.68), we obtain the error equations
Lemma 3.1
Let \(e_{1}\)–\(e_{4}\) satisfy (3.1)–(3.4). Then we have
Proof
Differentiating (3.1)–(3.2) with respect to t, we get
We choose \(\boldsymbol{v}=e_{3}\) in (3.6), \(w=-e_{4}\) in (3.7), \(\boldsymbol{v}=-e_{1t}\) in (3.3) and \(w=e_{2t}\) in (3.4), separately, then add up the four equations and obtain
We integrate (3.8) from 0 to t, use Gronwall’s inequality and the Cauchy inequality, then we obtain
where
Note that
then we have
Letting \(\boldsymbol{v}=e_{1}\) in (3.1), \(w=e_{2}\) in (3.2), \(\boldsymbol{v}=e_{3}\) in (3.3) and \(w=e_{4}\) in (3.4), respectively. We get
Differentiating (3.3)–(3.4) and (3.6)–(3.7) with respect to t, we get
We choose \(v=-e_{1tt}\) in (3.15), \(w=e_{2tt}\) in (3.16), \(v=e_{3t}\) in (3.17), \(w=-e_{4t}\) in (3.18), separately. We derive the following after addition for four equations:
Similar to (3.9), we derive
Taking \(t=0\) and \(w=e_{2tt}(0)\) in (3.4) leads to
Note that
At last, setting \(w=\operatorname {div}e_{1}\) and \(w=\operatorname {div}e_{3}\) in (3.2) and (3.4), we get
Thus, using (3.9)–(3.14) and (3.20)–(3.24), we complete the proof. □
By (2.59)–(2.62) and (2.69)–(2.72), we obtain the error equations
Lemma 3.2
Let \(e_{5}\)–\(e_{8}\) satisfy (3.25)–(3.28). Then we get
Proof
At first, setting \(t=T\) in (2.69)–(2.70) and (3.25)–(3.26), we derive
and
Differentiating (3.25)–(3.26) with respect to t, we obtain
Let \(\boldsymbol{v}=-e_{7}\) in (3.32), \(w=e_{8}\) in (3.33), \(\boldsymbol{v}=e_{5t}\) in (3.27) and \(w=-e_{6t}\) in (3.28), separately. After adding up the new equations, we have
Integrating (3.34) from t to T, from (3.30), Gronwall’s inequality and the Cauchy inequality, it is easy to see that
Letting \(\boldsymbol{v}=e_{7}\) in (3.27), we get
Next, for (3.25), we differentiate two times with respect to t, and set \(\boldsymbol{v}=e_{7}\). for (3.26), we also differentiate two times with respect to t, and set \(w=e_{8}\). For (3.27), we set \(\boldsymbol{v}=e_{5tt}\). For (3.28), we set \(w=\operatorname {div}e_{7}\). Combining the new four equalities, we derive
At last, similar to (3.13)–(3.14), (3.23)–(3.24) and (3.36), we have
Thus, combining Lemma 3.1, (3.31), (3.35)–(3.40) and (3.5), we complete the proof. □
Choosing \(\tilde{u}=u\) and \(\tilde{u}=u_{h}\) in (2.53)–(2.64), respectively, we have the error equations
Similar to Lemmas 3.1 and 3.2, Lemma 3.3 is given below.
Lemma 3.3
Let \(r_{1}\)–\(r_{8}\) satisfy (3.40)–(3.47). Then we have
where ϵ is an arbitrary small positive constant.
Lemma 3.4
[15] Let \((\tilde{\boldsymbol{p}},y,\boldsymbol{p},\tilde{y}, \tilde{\boldsymbol{q}},z,\boldsymbol{q},\tilde{z},u)\) and \((\tilde{\boldsymbol{p}}_{h},y _{h},\boldsymbol{p}_{h},\tilde{y}_{h},\tilde{\boldsymbol{q}}_{h},z_{h},\boldsymbol{q}_{h},u _{h})\) be the solutions of (2.10)–(2.22) and (2.30)–(2.42), respectively. Suppose that \((u_{h}+z_{h})\vert _{ \tau }\in H^{1}(\tau )\) and that there exists \(w\in K_{h}\) such that
where
Now, by Lemmas 3.1–3.3, the important result of this paper is given as follows.
Theorem 3.1
Let \((y,\tilde{\boldsymbol{p}},\tilde{y},\boldsymbol{p},z,\tilde{\boldsymbol{q}}, \tilde{z},\boldsymbol{q},u)\) and \((y_{h},\tilde{\boldsymbol{p}}_{h},\tilde{y}_{h},\boldsymbol{p}_{h},z_{h},\tilde{\boldsymbol{q}}_{h}, \tilde{z}_{h},\boldsymbol{q}_{h},u_{h})\) be the solutions of (2.9)–(2.19) and (2.26)–(2.36), respectively. Then we have
Proof
From Lemma 2.1 and (2.43), we have
For sufficiently small ϵ, using Lemmas 3.1–3.3 and (3.35), (3.53)–(3.54), we complete the proof. □
4 Conclusion and future work
In the article, using semidiscrete Raviart–Thomas mixed finite element methods, we studied fourth order hyperbolic equations of quadratic problems for optimal control, and then got the posteriori error estimates. In subsequent work, an a posteriori estimation will be considered by a fully discrete approximation of the mixed finite element. Of course, the error estimates of the same problems certainly also can be discussed with nonlinear fourth order hyperbolic equations.
References
Arada, N., Casas, E., Tröltzsch, F.: Error estimates for the numerical approximation of a semilinear elliptic control problem. Comput. Optim. Appl. 23, 201–229 (2002)
Babuška, I., Strouboulis, T.: The Finite Element Method and Its Reliability. Oxford University Press, Oxford (2001)
Brezzi, F., Fortin, M.: Mixed and Hybrid Finite Element Methods. Springer, Berlin (1991)
Brunner, H., Yan, N.: Finite element methods for optimal control problems governed by integral equations and integro-differential equations. Numer. Math. 101, 1–27 (2005)
Cao, W., Yang, D.: Ciarlet–Raviart mixed finite element approximation for an optimal control problem governed by the first bi-harmonic equation. J. Comput. Appl. Math. 233(2), 372–388 (2009)
Chen, Y.: Superconvergence of quadratic optimal control problems by triangular mixed finite elements. Int. J. Numer. Methods Eng. 75, 881–898 (2008)
Chen, Y., Huang, Y., Liu, W.B., Yan, N.N.: Error estimates and superconvergence of mixed finite element methods for convex optimal control problems. J. Sci. Comput. 42, 382–403 (2009)
Chen, Y., Liu, W.B.: A posteriori error estimates for mixed finite element solutions of convex optimal control problems. J. Comput. Appl. Math. 211, 76–89 (2008)
Chen, Y., Sun, C.M.: Error estimates and superconvergence of mixed finite element methods for fourth order hyperbolic control problems. Appl. Math. Comput. 244, 642–653 (2014)
Douglas, J., Roberts, J.E.: Global estimates for mixed finite element methods for second order elliptic equations. Math. Comput. 44, 39–52 (1985)
Gong, W., Yan, N.: A posteriori error estimate for boundary control problems governed by the parabolic partial differential equations. J. Comput. Math. 27, 68–88 (2009)
Haslinger, J., Neittaanmaki, P.: Finite Element Approximation for Optimal Shape Design. Wiley, Chichester (1989)
Hou, L., Turner, J.C.: Analysis and finite element approximation of an optimal control problem in electrochemistry with current density controls. Numer. Math. 71, 289–315 (1995)
Hou, T.: Error estimates of mixed finite element approximations for a class of fourth order elliptic control problems. Bull. Korean Math. Soc. 4(50), 1127–1144 (2013)
Hou, T.: A posteriori \(L^{\infty }(L^{2})\)-error estimates of semidiscrete mixed finite element methods for hyperbolic optimal control problems. Bull. Korean Math. Soc. 50, 321–341 (2013)
Knowles, G.: Finite element approximation of parabolic time optimal control problems. SIAM J. Control Optim. 20, 414–427 (1982)
Li, R., Liu, W., Ma, H., Tang, T.: Adaptive finite element approximation of elliptic control problems. SIAM J. Control Optim. 41, 1321–1349 (2002)
Lions, J.: Optimal Control of Systems Governed by Partial Differential Equations. Springer, Berlin (1971)
Lions, J., Magenes, E.: Non Homogeneous Boundary Value Problems and Applications. Grandlehre, vol. 181. Springer, Berlin (1972)
Liu, W., Ma, H., Tang, T., Yan, N.: A posteriori error estimates for discontinuous Galerkin time-stepping method for optimal control problems governed by parabolic equations. SIAM J. Numer. Anal. 42, 1032–1061 (2004)
Liu, W., Yan, N.: A posteriori error estimates for convex boundary control problems. SIAM J. Numer. Anal. 39, 73–99 (2001)
Liu, W., Yan, N.: A posteriori error estimates for optimal control problems governed by Stokes equations. SIAM J. Numer. Anal. 40, 1850–1869 (2003)
Mcknight, R., Bosarge, Jr., W.: The Ritz–Galerkin procedure for parabolic control problems. SIAM J. Control Optim. 11, 510–524 (1973)
Memon, S., Nataraj, N., Pani, A.K.: An a posteriori error analysis of mixed finite element Galerkin approximations to second order linear parabolic problems. SIAM J. Numer. Anal. 50, 1367–1393 (2012)
Neittaanmaki, P., Tiba, D.: Optimal Control of Nonlinear Parabolic Systems: Theory, Algorithms and Applications. Dekker, New York (1994)
Xing, X., Chen, Y.: Error estimates of mixed methods for optimal control problems governed by parabolic equations. Int. J. Numer. Methods Eng. 75, 735–754 (2008)
Acknowledgements
The authors express their thanks to the referees for their helpful suggestions, which led to improvements of the presentation.
Availability of data and materials
Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.
Funding
This work is supported by Youth Innovative Talents Project (Natural Science) of research on humanities and social sciences in Guangdong normal university (2017KQNCX265), The issue for the 13th Five-Year plan for the development of philosophy and social sciences in Guangzhou of 2018 (2018GZGJ168), School projects of Huashang College Guangdong University of Finance and Economics.
Author information
Authors and Affiliations
Contributions
CH, ZG and LG participated in the sequence alignment and drafted the manuscript. All authors read and approved the final manuscript.
Corresponding author
Ethics declarations
Competing interests
The authors declare that they have no competing interests.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
About this article
Cite this article
Hou, C., Guo, Z. & Guo, L. A posteriori error estimates for fourth order hyperbolic control problems by mixed finite element methods. Bound Value Probl 2019, 90 (2019). https://doi.org/10.1186/s13661-019-1204-2
Received:
Accepted:
Published:
DOI: https://doi.org/10.1186/s13661-019-1204-2
MSC
- 49J20
- 65N30
Keywords
- A posteriori error estimates
- Optimal control problems
- Fourth order hyperbolic equations
- Mixed finite element methods