Numerical Solution for Classical Optimal Control Problem Governing by Hyperbolic Partial Differential Equation via Galerkin Finite Element-Implicit method with Gradient Projection Method

Authors

  • Jamil A. Ali Al-Hawasy
  • Eman H. Al-Rawdanee

DOI:

https://doi.org/10.30526/32.2.2141

Keywords:

Numerical classical optimal control, hyperbolic boundary value problem, finite element method, Gradient Projection method, Armijo step search method, Optimal step method.

Abstract

     This paper deals with the numerical solution of the discrete classical optimal control problem (DCOCP) governing by linear hyperbolic boundary value problem (LHBVP). The method which is used here consists of: the GFEIM " the Galerkin finite element method in space variable with the implicit finite difference method in time variable" to find the solution of the discrete state equation (DSE) and the solution of its corresponding discrete adjoint equation, where a discrete classical control (DCC) is given.  The gradient projection method with either the Armijo method (GPARM) or with the optimal method (GPOSM) is used to solve the minimization problem which is obtained from the necessary condition for optimality of the DCOCP to find the DCC.An algorithm is given and a computer program is coded using the above methods to find the numerical solution of the DCOCP with step length of space variable   , and step length of time variable . Illustration examples are given to explain the efficiency of these methods. The results show the methods which are used here are better than those obtained when we used the Gradient method (GM) or Frank Wolfe method (FWM) with Armijo step search method to solve the minimization problem.

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Published

20-May-2019

Issue

Section

Mathematics

How to Cite

[1]
Ali Al-Hawasy, J.A. and Al-Rawdanee, E.H. 2019. Numerical Solution for Classical Optimal Control Problem Governing by Hyperbolic Partial Differential Equation via Galerkin Finite Element-Implicit method with Gradient Projection Method. Ibn AL-Haitham Journal For Pure and Applied Sciences. 32, 2 (May 2019), 71–80. DOI:https://doi.org/10.30526/32.2.2141.