Skip to main content
Log in

Optimal control of a class of reaction–diffusion systems

  • Published:
Computational Optimization and Applications Aims and scope Submit manuscript

Abstract

The optimal control of a system of nonlinear reaction–diffusion equations is considered that covers several important equations of mathematical physics. In particular equations are covered that develop traveling wave fronts, spiral waves, scroll rings, or propagating spot solutions. Well-posedness of the system and differentiability of the control-to-state mapping are proved. Associated optimal control problems with pointwise constraints on the control and the state are discussed. The existence of optimal controls is proved under weaker assumptions than usually expected. Moreover, necessary first-order optimality conditions are derived. Several challenging numerical examples are presented that include in particular an application of pointwise state constraints where the latter prevent a moving localized spot from hitting the domain boundary.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Alonso, S., Bär, M.: Reentry near the percolation threshold in a heterogeneous discrete model for cardiac tissue. Phys. Rev. Lett. 110(15), 158,101 (2013)

    Article  Google Scholar 

  2. Bode, M., Liehr, A.W., Schenk, C.P., Purwins, H.G.: Interaction of dissipative solitons: particle-like behaviour of localized structures in a three-component reaction–diffusion system. Physica D 161(1), 45–66 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  3. Borzì, A., Griesse, R.: Distributed optimal control of lambda–omega systems. J. Numer. Math. 14(1), 17–40 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  4. Buchholz, R., Engel, H., Kammann, E., Tröltzsch, F.: On the optimal control of the Schlögl model. Comput. Optim. Appl. 56, 153–185 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  5. Casas, E.: Boundary control of semilinear elliptic equations with pointwise state constraints. SIAM J. Control Optim. 31(4), 993–1006 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  6. Casas, E.: Pontryagin’s principle for state-constrained boundary control problems of semilinear parabolic equations. SIAM J. Control Optim. 35(4), 1297–1327 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  7. Casas, E., Kunisch, K.: Parabolic control problems in space–time measure spaces. ESAIM Control Optim. Calc. Var. 22(2), 355–370 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  8. Casas, E., Mateos, M., Rösch, A.: Approximation of sparse parabolic control problems. Math. Control Relat. Fields 7(3), 393–417 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  9. Casas, E., Mateos, M., Vexler, B.: New regularity results and improved error estimates for optimal control problems with state constraints. ESAIM Control Optim. Calc. Var. 20, 803–822 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  10. Casas, E., Raymond, J., Zidani, H.: Pontryagin’s principle for local solutions of control problems with mixed control-state constraints. SIAM J. Control Optim. 39(4), 1182–1203 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  11. Casas, E., Ryll, C., Tröltzsch, F.: Sparse optimal control of the Schlögl and FitzHugh–Nagumo systems. Comput. Methods Appl. Math. 13, 415–442 (2014)

    Google Scholar 

  12. Casas, E., Ryll, C., Tröltzsch, F.: Second order and stability analysis for optimal sparse control of the FitzHugh–Nagumo equation. SIAM J. Control Optim. 53(4), 2168–2202 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  13. Kunisch, K., Wagner, M.: Optimal control of the bidomain system (iii): existence of minimizers and first-order optimality conditions. ESAIM Math. Model. Numer. Anal. 47(4), 1077–1106 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  14. Kuramoto, Y.: Chemical Oscillations, Waves, and Turbulence, Springer Series in Synergetics, vol. 19. Springer, Berlin (1984)

    Book  MATH  Google Scholar 

  15. Ladyzhenskaya, O., Solonnikov, V., Ural’tseva, N.: Linear and Quasilinear Equations of Parabolic Type. American Mathematical Society, Providence (1988)

    MATH  Google Scholar 

  16. Löber, J.: Nonlinear excitation waves in spatially heterogenous reaction–diffusion systems. Technical report, TU Berlin, Institute of Theoretical Physics (2009)

  17. Löber, J.: Optimal trajectory tracking. Ph.D. thesis, TU Berlin (2015)

  18. Löber, J.: Exactly realizable desired trajectories. arXiv preprint arXiv:1603.00611 (2016)

  19. Löber, J., Engel, H.: Controlling the position of traveling waves in reaction–diffusion systems. Phys. Rev. Lett. 112(14), 148,305 (2014)

    Article  Google Scholar 

  20. Mihaliuk, E., Sakurai, T., Chirila, F., Showalter, K.: Feedback stabilization of unstable propagating waves. Phys. Rev. E 65(6), 065,602 (2002)

    Article  Google Scholar 

  21. Mikhailov, A.S., Showalter, K.: Control of waves, patterns and turbulence in chemical systems. Phys. Rep. 425(2), 79–194 (2006)

    Article  MathSciNet  Google Scholar 

  22. Murray, J.D.: Mathematical Biology, Biomathematics, vol. 19, 2nd edn. Springer, Berlin (1993)

    Book  Google Scholar 

  23. Ryll, C.: Optimal control of patterns in some reaction–diffusion-systems. Ph.D. thesis, Technical University of Berlin (2016). https://doi.org/10.14279/depositonce-5712

  24. Ryll, C., Löber, J., Martens, S., Engel, H., Tröltzsch, F.: Analytical, optimal, and sparse optimal control of traveling wave solutions to reaction–diffusion systems. In: Schöll, E., Klapp, S., Hövel, P. (eds.) Understanding Complex Systems, Control of Self-organizing Nonlinear Systems, pp. 189–210. Springer, Berlin (2016)

    Chapter  Google Scholar 

  25. Sakurai, T., Mihaliuk, E., Chirila, F., Showalter, K.: Design and control of wave propagation patterns in excitable media. Science 296(5575), 2009–2012 (2002)

    Article  Google Scholar 

  26. Schenk, C.P., Or-Guil, M., Bode, M., Purwins, H.G.: Interacting pulses in three-component reaction–diffusion systems on two-dimensional domains. Phys. Rev. Lett. 78(19), 3781 (1997)

    Article  Google Scholar 

  27. Schlesner, J., Zykov, V.S., Brandtstädter, H., Gerdes, I., Engel, H.: Efficient control of spiral wave location in an excitable medium with localized heterogeneities. New J. Phys. 10(1), 015,003 (2008)

    Article  Google Scholar 

  28. Schlögl, F.: A characteristic critical quantity in nonequilibrium phase transitions. Z. Phys. B Condens. Matter. 52, 51–60 (1983)

    Article  Google Scholar 

  29. Schöll, E., Schuster, H.: Handbook of Chaos Control. Wiley-VCH, Weinheim (2008)

    MATH  Google Scholar 

  30. Showalter, R.E.: Monotone Operators in Banach Space and Nonlinear Partial Differential Equations. Mathematical Surveys and Monographs, vol. 49. American Mathematical Society, Providence, RI (1997)

    MATH  Google Scholar 

  31. Smoller, J.: Shock Waves and Reaction–Diffusion Equations, Grundlehren der Mathematischen Wissenschaften [Fundamental Principles of Mathematical Sciences], vol. 258, 3rd edn. Springer, New York (1994)

    Google Scholar 

  32. Zykov, V.S., Bordiougov, G., Brandtstädter, H., Gerdes, I., Engel, H.: Global control of spiral wave dynamics in an excitable domain of circular and elliptical shape. Phys. Rev. Lett. 92(1), 018,304 (2004)

    Article  Google Scholar 

  33. Zykov, V.S., Engel, H.: Feedback-mediated control of spiral waves. Physica D 199(1–2), 243–263 (2004)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Fredi Tröltzsch.

Additional information

Eduardo Casas was partially supported by the Spanish Ministerio de Economía, Industria y Competitividad under Projects MTM2014-57531-P and MTM2017-83185-P. Christopher Ryll and Fredi Tröltzsch are supported by DFG in the framework of the Collaborative Research Center SFB 910, Project B6.

Appendix: Proof of Lemma 3.1

Appendix: Proof of Lemma 3.1

Let us consider sequences \(\{f_k\}_{k=1}^\infty \subset L^2(Q)^n\), \(\{g_k\}_{k=1}^\infty \subset L^2(\varSigma )^n\), and \(\{h_k\}_{k = 1}^\infty \subset H^1(\varOmega )^n\) satisfying

$$\begin{aligned}&\Vert f_k\Vert _{L^1(Q)^n} \le \Vert \nabla _yg(\cdot ,\cdot ,{{\bar{y}}}){{\bar{\mu }}}_Q \Vert _{{\mathcal {M}}(Q)^n},\ f_k {\mathop {\rightharpoonup }\limits ^{*}} \nabla _yg(\cdot ,\cdot ,{{\bar{y}}}){{\bar{\mu }}}_Q \quad \text { in } {\mathcal {M}}(Q)^n, \end{aligned}$$
(5.1)
$$\begin{aligned}&\Vert g_k\Vert _{L^1(\varSigma )^n} \le \Vert \nabla _yg(\cdot ,\cdot ,{{\bar{y}}}){{\bar{\mu }}}_\varSigma \Vert _{{\mathcal {M}}(\varSigma )^n},\ g_k {\mathop {\rightharpoonup }\limits ^{*}} \nabla _yg(\cdot ,\cdot ,{{\bar{y}}}){{\bar{\mu }}}_\varSigma \quad \text { in } {\mathcal {M}}(\varSigma )^n, \end{aligned}$$
(5.2)
$$\begin{aligned}&\left\{ \begin{array}{l}\displaystyle \Vert h_k\Vert _{L^1(\varOmega )^n} \le \Vert \nabla _yg(\cdot ,T,{{\bar{y}}}(T)){{\bar{\mu }}}_\varOmega \Vert _{{\mathcal {M}}({{\bar{\varOmega }}} \times \{T\})^n}\\ h_k {\mathop {\rightharpoonup }\limits ^{*}} \nabla _yg(\cdot ,T,{{\bar{y}}}(T)) {{\bar{\mu }}}_\varOmega \text { in } {\mathcal {M}}({{\bar{\varOmega }}} \times \{T\})^n.\end{array}\right. \end{aligned}$$
(5.3)

We also consider a sequence \(\{w_k\}_{k= 1}^\infty \subset H^1(\varOmega )^n\) such that

$$\begin{aligned} \left\{ \begin{array}{l}\displaystyle w_k \rightarrow C^\top _\varOmega [C_\varOmega {{\bar{y}}}(\cdot ,T) - y_\varOmega ] \ \text { strongly in } L^2(\varOmega )^n\\ \displaystyle \text {and } \Vert w_k\Vert _{L^2(\varOmega )^n} \le \Vert C^\top _\varOmega [C_\varOmega {{\bar{y}}}(\cdot ,T) - y_\varOmega ]\Vert _{L^2(\varOmega )^n}\quad \forall k. \end{array}\right. \end{aligned}$$
(5.4)

Now we consider the problem

$$\begin{aligned} \left\{ \begin{array}{ll} \displaystyle -\frac{\partial \varphi _k}{\partial t} - \varDelta \varphi _k + \frac{\partial R}{\partial y}(\cdot ,\cdot ,{{\bar{y}}})\varphi _k + A^\top \varphi _k = C_Q^\top [C_Q{{\bar{y}}} - y_Q] + f_k&{}\quad \text {in }Q,\\ \displaystyle \partial _\nu \varphi _k = \displaystyle g_k&{}\quad \text {on } \varSigma , \\ \varphi _k(\cdot ,T) = w_k + h_k&{}\quad \text {in } {{\bar{\varOmega }}}. \end{array}\right. \end{aligned}$$
(5.5)

This is a standard linear problem for which existence and uniqueness of a solution \(\varphi _k \in W(0,T)^n\) are well known. Moreover, since \(w_k + h_k \in H^1(\varOmega )^n\), we also have that \(\varphi _k \in H^1(Q)^n\). From Theorem 3.3 we infer that

$$\begin{aligned} \varphi _k \rightharpoonup {{\bar{\varphi }}} \ \text { in } L^r\left( 0,T;W_0^{1,s}(\varOmega )\right) ^n\quad \forall r, s \in [1, 2) \text { with } \frac{2}{r}+\frac{d}{s} > 1 + d. \end{aligned}$$
(5.6)

Moreover, the following strong convergence holds [7]

$$\begin{aligned} \lim _{k \rightarrow \infty }\Vert {{\bar{\varphi }}} - \varphi _k\Vert _{L^q(Q)^n} = 0\quad \forall 1\le q < \frac{d + 2}{d}. \end{aligned}$$
(5.7)

Now, we define \(\varphi _{M,k}(x,t) = {\text {Proj}}_{[-M,+M]^n}({{\bar{\varphi }}}_k(x,t))\). Since \(\varphi _k \in H^1(Q)^n\), then we also have that \(\varphi _{M,k} \in H^1(Q)^n\). From the inequality \(|\varphi _{M}(x,t) - \varphi _{M,k}(x,t)| \le |{{\bar{\varphi }}}(x,t) - \varphi _{k}(x,t)|\) and (5.7) we infer that \(\varphi _{M,k} \rightarrow \varphi _M\) strongly in \(L^q(Q)^n\) for every \(1\le q < \frac{d + 2}{d}\).

If we prove that \(\{\varphi _{M,k}\}_{k = 1}^\infty \) is bounded in \(L^2(0,T;H^1(\varOmega ))^n\), then the convergence \(\varphi _{M,k} \rightarrow \varphi _M\) in \(L^q(Q)^n\) implies that \(\varphi _M \in L^2(0,T;H^1(\varOmega ))^n\) as well. Taking \(\eta = |C_R| + 1\), multiplying (5.5) by \({\mathrm{e}}^{2\eta t}\varphi _{M,k}\) and integrating in Q

$$\begin{aligned}&\int _Q-{\mathrm{e}}^{2\eta t}\frac{\partial \varphi _k}{\partial t}\cdot \varphi _{M,k}\, dx\, dt + \int _Q{\mathrm{e}}^{2\eta t}\nabla \varphi _k \cdot \nabla \varphi _{M,k}\, dx\, dt\nonumber \\&\quad + \int _Q{\mathrm{e}}^{2\eta t}\left( \frac{\partial R}{\partial y}(x,t,{{\bar{y}}})\varphi _k\right) \cdot \varphi _{M,k}\, dx\, dt + \int _Q{\mathrm{e}}^{2\eta t}\varphi _k^\top A(x,t)\varphi _{M,k}\, dx\, dt\nonumber \\&\qquad = \int _Q{\mathrm{e}}^{2\eta t}\left( C_Q^\top [C_Q{{\bar{y}}} - y_Q] + f_k\right) \cdot \varphi _{M,k}\, dx\, dt+ \int _\varSigma {\mathrm{e}}^{2\eta t} g_k\cdot \varphi _{M,k}\, dx\, dt. \end{aligned}$$
(5.8)

Now using that \(\varphi _k\cdot \partial _t\varphi _{M,k} = \varphi _{M,k}\cdot \partial _t\varphi _{M,k} = \frac{1}{2}\partial _t|\varphi _{M,k}|^2\), we obtain

$$\begin{aligned} \int _Q-\text {e}^{2\eta t}\frac{\partial \varphi _k}{\partial t}\cdot \varphi _{M,k}\, dx\, dt =&-\int _0^T\frac{d}{dt}\int _\varOmega \text {e}^{2\eta t}\varphi _k\cdot \varphi _{M,k}\, dx\, dt\nonumber \\&+ 2\eta \int _Q\text {e}^{2\eta t}\varphi _k\cdot \varphi _{M,k}\, dx\, dt + \int _Q\text {e}^{2\eta t}\varphi _k\cdot \frac{\partial \varphi _{M,k}}{\partial t}\, dx\, dt\nonumber \\ =&-\int _\varOmega \text {e}^{2\eta T}\varphi _k(x,T)\cdot \varphi _{M,k}(x,T)\, dx \nonumber \\&+ \int _\varOmega \varphi _k(x,0)\cdot \varphi _{M,k}(x,0)\, dx\nonumber \\&+ 2\eta \int _Q\text {e}^{2\eta t}\varphi _k\cdot \varphi _{M,k}\, dx\, dt +\frac{1}{2}\int _Q\text {e}^{2\eta t}\partial _t|\varphi _{M,k}|^2\, dx\, dt. \end{aligned}$$
(5.9)

For the last term we have

$$\begin{aligned}&\frac{1}{2}\int _Q\text {e}^{2\eta t}\partial _t|\varphi _{M,k}|^2\, dx\, dt\nonumber \\&\quad = \frac{1}{2}\int _0^T\frac{d}{dt}\int _\varOmega \text {e}^{2\eta t}|\varphi _{M,k}|^2\, dx\, dt - \eta \int _0^T\int _\varOmega \text {e}^{2\eta t}|\varphi _{M,k}|^2\, dx\, dt\nonumber \\&\quad \ge \frac{1}{2}\int _\varOmega \text {e}^{2\eta T}|\varphi _{M,k}(x,T)|^2\, dx - \frac{1}{2}\int _\varOmega |\varphi _{M,k}(x,0)|^2\, dx \nonumber \\&\qquad - \eta \int _Q\text {e}^{2\eta t}\varphi _k\cdot \varphi _{M,k}\, dx\, dt. \end{aligned}$$
(5.10)

From (5.9) and (5.10) and using that \(\varphi _k\cdot \varphi _{M,k} \ge |\varphi _{M,k}|^2\) we deduce

$$\begin{aligned} \int _Q-\text {e}^{2\eta t}\frac{\partial \varphi _k}{\partial t}\cdot \varphi _{M,k}\, dx\, dt \ge&-\text {e}^{2\eta T}\int _\varOmega (w_k + h_k)\cdot \varphi _{M,k}(x,T)\, dx\\&+ \frac{1}{2}\int _\varOmega |\varphi _{M,k}(x,0)|^2\, dx + \eta \int _Q\text {e}^{2\eta t}\varphi _k\cdot \varphi _{M,k}\,dx\, dt\\&+ \frac{\text {e}^{2\eta T}}{2}\int _\varOmega |\varphi _{M,k}(x,T)|^2\, dx\\ \ge&-\text {e}^{2\eta T}\int _\varOmega (w_k + h_k)\cdot \varphi _{M,k}(x,T)\, dx \\&+ \eta \int _Q\text {e}^{2\eta t}\varphi _k\cdot \varphi _{M,k}\, dx\, dt\\&+ \frac{1}{2}\int _\varOmega |\varphi _{M,k}(x,T)|^2\, dx. \end{aligned}$$

Inserting this inequality in (5.8) and taking into account that \(\partial _{x_i}\varphi _k\cdot \partial _{x_i}\varphi _{M,k} = \partial _{x_i}\varphi _{M,k}\cdot \partial _{x_i}\varphi _{M,k}\), we obtain with Young’s inequality, (5.1)–(5.4), and the estimate for \(\Vert \varphi _k\Vert _{L^1(Q)^n}\) derived from Theorem 3.3

$$\begin{aligned}&\int _Q|\nabla \varphi _{M,k}|^2\, dx\, dt + \int _Q|\varphi _{M,k}|^2\, dx\, dt + \frac{1}{2}\int _\varOmega |\varphi _{M,k}(x,T)|^2\, dx\\&\quad \le \int _Q|\nabla \varphi _{M,k}|^2 dx dt + \int _Q\text {e}^{2\eta t}(\eta -|C_R|)\varphi _k\cdot \varphi _{M,k}\, dx dt+\frac{1}{2}\int _\varOmega |\varphi _{M,k}(\cdot ,T)|^2 dx \\&\quad \le \int _0^{T}-{\mathrm{e}}^{2\eta t}\frac{\partial \varphi _M}{\partial t}\cdot \varphi _{M,k}\, dx\, dt + \int _Q\text {e}^{2\eta t}\nabla \varphi _M \cdot \nabla \varphi _{M,k}\, dx\, dt\\&\qquad + \int _Q\text {e}^{2\eta t}\Big (\frac{\partial R}{\partial y}(x,t,{{\bar{y}}})\varphi _k\Big )\cdot \varphi _{M,k}\, dx\, dt + \text {e}^{2\eta T}\int _\varOmega (w_k + h_k)\cdot \varphi _{M,k}(x,T)\, dx\\&\quad = \int _Q\text {e}^{2\eta t}\Big (C_Q^\top [C_Q{{\bar{y}}} - y_Q] + f_k\Big )\cdot \varphi _{M,k}\, dx\, dt + \int _\varSigma {\mathrm{e}}^{2\eta t} g_k\cdot \varphi _{M,k}\, dx\, dt\\&\qquad + \text {e}^{2\eta T}\int _\varOmega (w_k + h_k)\cdot \varphi _{M,k}(T)\, dx - \int _Q{\mathrm{e}}^{2\eta t}\varphi _k^\top A(x,t)\varphi _{M,k}\, dx\, dt\\&\quad \le \text {e}^{2\eta T}\Big [\Vert C_Q^\top [C_Q{{\bar{y}}} - y_Q]\Vert _{L^2(Q)^n}\Vert \varphi _{M,k}\Vert _{L^2(Q)^n} + \Vert w_k\Vert _{L^2(\varOmega )^n}\Vert \varphi _{M,k}(T)\Vert _{L^2(\varOmega )^n}\\&\qquad + M\big (\Vert f_k\Vert _{L^1(Q)^n} + \Vert g_k\Vert _{L^1(\varSigma )^n} + \Vert h_k\Vert _{L^1(\varOmega )^n} + \Vert A\Vert _{L^\infty (Q,{\mathbb {R}}^{n \times n})}\Vert \varphi _k\Vert _{L^1(Q)^n)}\big )\Big ]\\&\quad \le C\Big [\Big \Vert C_Q^\top [C_Q{{\bar{y}}} - y_Q]\Big \Vert ^2_{L^2(Q)} + \Vert C^\top _\varOmega [C_\varOmega {{\bar{y}}}(\cdot ,T) - y_\varOmega ]\Vert ^2_{L^2(\varOmega )^n}\\&\qquad + M\Vert \nabla _yg(\cdot ,\cdot ,{{\bar{y}}})\Vert _{C(K)^n}\Vert {{\bar{\mu }}}_Q\Vert _{{\mathcal {M}}({{\bar{Q}}})}\Big ] + \frac{1}{2}\int _Q|\varphi _{M,k}|^2 dx dt + \frac{1}{4}\Vert \varphi _{M,k}(T)\Vert ^2_{L^2(\varOmega )^n}. \end{aligned}$$

Finally, we get from the above inequality with (5.4) that each \(\varphi _{M,k}\) satisfies (3.15). Hence, \(\varphi _M\) also does it. \(\square \)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Casas, E., Ryll, C. & Tröltzsch, F. Optimal control of a class of reaction–diffusion systems. Comput Optim Appl 70, 677–707 (2018). https://doi.org/10.1007/s10589-018-9986-1

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10589-018-9986-1

Keywords

Navigation