Ningning Yan

Local A Posteriori Error Estimates for Convex Boundary Control Problems

In this paper, we derive some improved a posteriori error estimates for finite element approximation of Neumann boundary control problems. We first establish local upper a posteriori error estimates for both the state and the control approximation of the general convex boundary control problems. We then derive local upper and lower a posteriori error estimates for a class of control problems that frequently appear in applications.

A Posteriori Error Estimates for Control Problems Governed by Stokes Equations

In this paper, we derive a posteriori error estimates for the finite element approximation of distributed optimal control problems governed by the Stokes equations. We obtain a posteriori error estimators for both the state and the control approximation in the L2 norm and the H1 norm. These estimates can be used to construct reliable adaptive finite element approximation for the control problems.

Error Estimates and Superconvergence of Mixed Finite Element Methods for Convex Optimal Control Problems

In this paper, we investigate the discretization of general convex optimal control problem using the mixed finite element method. The state and co-state are discretized by the lowest order Raviart-Thomas element and the control is approximated by piecewise constant functions. We derive error estimates for both the control and the state approximation. Moreover, we present the superconvergence analysis for mixed finite element approximation of the optimal control problem. Finally, some numerical examples are given to demonstrate the practical side of the theoretical results about superconvergence.

Gradient recovery type a posteriori error estimates for finite element approximations on irregular meshes

In this paper, the gradient recovery type a posteriori error estimators for finite element approximations are proposed for irregular meshes. Both the global and the local a posteriori error estimates are derived. Moreover, it is shown that the a posteriori error estimates is asymptotically exact on where the mesh is regular enough and the exact solution is smooth.

A posteriori error estimates for discontinuous Galerkin time-stepping method for optimal control problems governed by parabolic equations

In this paper, we examine the discontinuous Galerkin (DG) finite element approximation to convex distributed optimal control problems governed by linear parabolic equations, where the discontinuous finite element method is used for the time discretization and the conforming finite element method is used for the space discretization. We derive a posteriori error estimates for both the state and the control approximation, assuming only that the underlying mesh in space is nondegenerate. For problems with control constraints of obstacle type, which are the kind most frequently met in applications, further improved error estimates are obtained.

A posteriori error estimates for control problems governed by nonlinear elliptic equations

In this paper, we derive a posteriori error estimates for the finite element approximation of a class of nonlinear optimal control problems. We derive a posteriori error estimates for both the state and the control approximation. Such estimates, which are apparently not available in the literature, can be used to construct reliable adaptive finite element approximation schemes for the control problems.

Quasi-Norm Local Error Estimators for p -Laplacian

In this paper, we extend the quasi-norm techniques used in a priori error estimation of finite element approximation of degenerate nonlinear systems in order to carry out an improved a posteriori error analysis for the p-Laplacian. We derive quasi-norm a posteriori error estimators of residual type, which are shown to provide improved upper and lower bounds on the discretization error. For sufficiently regular solutions, these estimators are further shown to be equivalent on the discretization error in a quasi norm. Numerical results demonstrating these a posteriori estimators are also presented.

A Posteriori Error Estimates of Recovery Type for Distributed Convex Optimal Control Problems

Abstract In this paper, we derive a posteriori error estimates of recovery type, and present the superconvergence analysis for the finite element approximation of distributed convex optimal control problems. We provide a posteriori error estimates of recovery type for both the control and the state approximation, which are generally equivalent. Under some stronger assumptions, they are further shown to be asymptotically exact. Such estimates, which are apparently not available in the literature, can be used to construct adaptive finite element approximation schemes and as a reliability bound for the control problems. Numerical results demonstrating our theoretical results are also presented in this paper.

A Mixed Finite Element Scheme for Optimal Control Problems with Pointwise State Constraints

In this paper, we propose a mixed variational scheme for optimal control problems with point-wise state constraints, the main idea is to reformulate the optimal control problems to a constrained minimization problem involving only the state, which is characterized by a fourth order variational inequality. Then mixed form based on this fourth order variational inequality is formulated and a direct numerical algorithm is proposed without the optimality conditions of underlying optimal control problems. The a priori and a posteriori error estimates are proved for the mixed finite element scheme. Numerical experiments confirm the efficiency of the new strategy.

A RT Mixed FEM/DG Scheme for Optimal Control Governed by Convection Diffusion Equations

In this paper, we provide a numerical scheme—RT mixed FEM/DG scheme for the constrained optimal control problem governed by convection dominated diffusion equations. A priori and a posteriori error estimates are obtained for both the state, the co-state and the control. The adaptive mesh refinement can be applied indicated by a posteriori error estimator provided in this paper. Numerical examples are presented to illustrate the theoretical analysis.