• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.19 no.4
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• pp.387-407
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• 2015

This paper analyzes the $h{\times}p$ version of the finite element method for optimal control problems constrained by elliptic partial differential equations with random inputs. The main result is that the $h{\times}p$ error bound for the control problems subject to stochastic partial differential equations leads to an exponential rate of convergence with respect to p as for the corresponding direct problems. Numerical examples are used to confirm the theoretical results.

• Bulletin of the Korean Mathematical Society
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• v.50 no.1
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• pp.321-341
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• 2013

In this paper, we discuss the a posteriori error estimates of the semidiscrete mixed finite element methods for quadratic optimal control problems governed by linear hyperbolic equations. The state and the co-state are discretized by the order $k$ Raviart-Thomas mixed finite element spaces and the control is approximated by piecewise polynomials of order $k(k{\geq}0)$. Using mixed elliptic reconstruction method, a posterior $L^{\infty}(L^2)$-error estimates for both the state and the control approximation are derived. Such estimates, which are apparently not available in the literature, are an important step towards developing reliable adaptive mixed finite element approximation schemes for the control problem.

• Journal of applied mathematics & informatics
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• v.31 no.3_4
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• pp.479-490
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• 2013

In this paper, we investigate a priori error estimates and superconvergence of varitional discretization for nonlinear parabolic optimal control problems with control constraints. The time discretization is based on the backward Euler method. The state and the adjoint state are approximated by piecewise linear functions and the control is not directly discretized. We derive a priori error estimates for the control and superconvergence between the numerical solution and elliptic projection for the state and the adjoint state and present a numerical example for illustrating our theoretical results.

• Bulletin of the Korean Mathematical Society
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• v.51 no.3
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• pp.847-862
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• 2014

Finite element approximation solutions of the optimal control problems for stochastic Stokes equations with the forcing term perturbed by white noise are considered. Error estimates are established for the fully coupled optimality system using Brezzi-Rappaz-Raviart theory. Numerical examples are also presented to examine our theoretical results.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.407-411
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• 1992

A method for optimal route planning is presented with the assumption that the overall defended area is known in terms of threat potential function. This approach employes tangent plane to reduce the dimension of the state space for optimal programming problems with a state equality constraint. One-dimensional search algorithm is used to select the optimal route among the extermal fields which are obtained by integrating three differential equations from the initial values. In addition to being useful for the route planning through threat potential area, the trajectory planning will be suitable for general two-dimensional searching problems.

• Bulletin of the Korean Mathematical Society
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• v.48 no.5
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• pp.1079-1092
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• 2011

We consider the Newton's method for an direct solver of the optimal control problems of the Navier-Stokes equations. We show that the finite element solutions of the optimal control problem for Stoke equations may be chosen as the initial guess for the quadratic convergence of Newton's algorithm applied to the optimal control problem for the Navier-Stokes equations provided there are sufficiently small mesh size h and the moderate Reynold's number.

• Journal of the Korean Mathematical Society
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• v.41 no.4
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• pp.681-715
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• 2004

Mathematical formulation and numerical solutions of an optimal Dirichlet boundary control problem for the Boussinesq equations are considered. The solution of the optimal control problem is obtained by adjusting of the temperature on the boundary. We analyze finite element approximations. A gradient method for the solution of the discrete optimal control problem is presented and analyzed. Finally, the results of some computational experiments are presented.

• Journal of applied mathematics & informatics
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• v.14 no.1_2
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• pp.97-113
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• 2004

In this paper we shall study moving boundary problems, and we introduce an approach for solving a wide range of them by using calculus of variations and optimization. First, we transform the problem equivalently into an optimal control problem by defining an objective function and artificial control functions. By using measure theory, the new problem is modified into one consisting of the minimization of a linear functional over a set of Radon measures; then we obtain an optimal measure which is then approximated by a finite combination of atomic measures and the problem converted to an infinite-dimensional linear programming. We approximate the infinite linear programming to a finite-dimensional linear programming. Then by using the solution of the latter problem we obtain an approximate solution for moving boundary function on specific time. Furthermore, we show the path of moving boundary from initial state to final state.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.50.2-50
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• 2001

Optimal control problems are notoriously difficult to solve either analytically or numerically except for limited cases of having simple dynamics. Evolutionary programming is a promising method of solving various optimal control problem arising in practice since it does not require the expression of Lagrange´s adjoint system and that it can easily implement the inequality constraints on the control variable, In this paper, evolutionary programming is combined with spline method, so the smoother control profile and the Jumping times could be obtained. The optimal profiles obtained by the proposed method are compared with exact solution if it is available. With more complicated model equation, the proposed method showed better performance than other researchers´. It is demonstrated that the evolutionary programming with spline method can ...

• Bulletin of the Korean Mathematical Society
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• v.50 no.4
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• pp.1127-1144
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• 2013

In this paper, we consider the error estimates of the numerical solutions of a class of fourth order linear-quadratic elliptic optimal control problems by using mixed finite element methods. The state and co-state are approximated by the order $k$ Raviart-Thomas mixed finite element spaces and the control variable is approximated by piecewise polynomials of order $k(k{\geq}1)$. $L^2$ and $L^{\infty}$-error estimates are derived for both the control and the state approximations. These results are seemed to be new in the literature of the mixed finite element methods for fourth order elliptic control problems.