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Numerical algorithms for solving an elliptic optimal control problem with a power-law nonlinearity

Hart L.1, Yatsechko N.1
1 Dniepropetrovsk National University named by Oles Honchar

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UDC: 519.8
Publication Language: Ukrainian
Stuc. intelekt. 2021; 26(2):64-76

Abstract: The paper is devoted to the development and analysis of approximation-iteration algorithms based on the method of grids and the method of lines for solving an elliptic optimal control problem with a power-law nonlinearity. For the numerical solution of the main boundary value problem and the adjoint one, the second order of accuracy difference schemes are applied using the implicit method of simple iteration. Computational schemes of the method of lines for solving the above-mentioned elliptic boundary value problems are implemented in combination with the shooting method for the approximate solution of boundary value problems for the corresponding ordinary differential equations systems arising in the considered domain after lattice approximation. To minimize the objective functional, well-known gradient-type methods (gradient projection and conditional gradient methods) of constrained optimization are used. The essence of the proposed approximation-iteration approach consists in replacing the original extremal problem with a sequence of grid problems that approximate it on a set of refining grids, and applying an iterative gradient-type method to each of the "approximate" extremal problems. In this case, we propose to construct only a few approximations to the solution for each of the "approximate" problems and to take the last of these approximations, using piecewise linear interpolation, as the initial approximation in the iterative process for the next "approximate" problem. The sequence of the corresponding piecewise linear interpolants is considered as a sequence of approximations to the solution of the original extremal problem. The paper discusses the theoretical foundations of this combined approach, as well as its advantages over traditional methods using the example of solving a model optimal control problem.

Keywords: optimal control problem, elliptic system, power-law nonlinearity, grid method, method of lines, approximation schemes.

References:

  1. Shevchenko A.I., Minenko A.S. (2012) Research methods for nonlinear mathematical models. К.: Nauk. dumka.
  2. Lions J.-L. (1971) Optimal control of systems governed by partial differential equations. Berlin: Springer-Verlag.
  3. Muravei L.A., Petrov V.M., Romanenkov A.M. (2018) Optimal control of nonlinear processes in problems of mathematical physics. M.: Publishing house MAI.
  4. Neittaanmaki P., Sprekels J., Tiba D. (2006) Optimization of elliptic systems: theory and applications. New York: Springer. doi: 10.1007/b138797
  5. Kogut O.P., Kogut P.I., Ryadno O.A. (2010) Optimization in nonlinear elliptic boundary value problems. Dnipropetrovsk: DDFA.
  6. Serovaiskiy S.Ya. (2006) Optimization and differentiation. T. 1. Minimization of functionals. Stationary systems. – Almaty: Print-S.
  7. Shevchenko A.I., Minenko A.S. (2015) Qualitative properties of solutions of one class of evolutionary systems. Reports of the National Academy of Sciences of Ukraine, 1, 36-40. doi: 10.15407/dopovidi2015.01.036
  8. Cindea N., Matei A., Micu S., Niţă C. (2020) Boundary optimal control for antiplane problems with power-law friction. Applied Mathematics and Computation, 386(6): 125448. doi: 10.1016/j.amc.2020.125448.
  9. Wang K., Zhao D., Feng B. (2018) Optimal nonlinearity control of Schrödinger equation. Evolution Equations and Control Theory, 7(2), 317-334. doi: 10.3934/eect.2018016.
  10. Serovaiskii S.Ya. (2010) The necessary optimality conditions for a nonlinear stationary system whose state functional is not differentiable with respect to the control. Russian Mathematics, 54(6), 26–38. doi: 10.3103/S1066369X10060046.
  11. Serovaiskiy S.Ya. (1984) An optimal control problem for an elliptic system with a power-law nonlinearity. Siberian Mathematical Journal, 25 (1), 120-125.
  12. Hervé Le D. (2018) Nonlinear elliptic partial differential equations: Аn introduction. – Cham: Springer.
  13. Serovaiskiy S.Ya. (1991) Necessary and sufficient conditions for optimality for a system described by a nonlinear elliptic equation. Siberian Mathematical Journal, 32 (3), 141–150.
  14. Samarskii A.A. (2001) The theory of difference schemes. New York: Marcel Dekker Inc.
  15. Lyashko A.D. (1972) Method of lines for quasilinear elliptic equations. Differential Equations, 8 (5), 891-901.
  16. Hart L.L. (2017) Projection-iteration methods for solving operator equations and problems of infinite-dimensional optimization. Dis. ... Dr. Phys.-Math. Sciences, 01.05.01, MES of Ukraine, Dnipro: DNU.
  17. Vasiliev F.P. (1974) Lectures on methods for solving extremal problems. M.: Publishing house of MSU.
  18. Balashova S.D., Tavadze L.L., Tavadze E.L. (1991) Application of projection-iteration methods to the solution of the Dirichlet problem for the Poisson equation. Dnepropetrovsk. Dep. in VINITI 13.06.91, No. 2486-B 91, 28 p.
  19. Stoer J., Bulirsch R. (2002) Introduction to Numerical Analysis. New York : Springer.
  20. Hart L.L., Polyakov M.V. (2004) Comparative analysis of iterative schemes of the method of lines for solving a weakly nonlinear elliptic problem. Problems of Applied Mathematics and Mathematical Modeling, 47-57.
  21. Balashova S.D., Tavadze E.L. (1996) On the convergence of the projection-iteration method for solving an extremal problem with constraints. Mathematical models and computational methods in applied problems, 1-8.

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