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Domain decomposition methods for advection dominated linear-quadratic elliptic optimal control problems

机译:对流占优的线性二次椭圆最优控制问题的区域分解方法

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We present an optimization-level domain decomposition (DD) preconditioner for the solution of advection dominated elliptic linear-quadratic optimal control problems, which arise in many science and engineering applications. The DD preconditioner is based on a decomposition of the optimality conditions for the elliptic linear-quadratic optimal control problem into smaller subdomain optimality conditions with Dirichlet boundary conditions for the states and the adjoints on the subdomain interfaces. These subdomain optimality conditions are coupled through Robin transmission conditions for the states and the adjoints. The parameters in the Robin transmission condition depend on the advection. This decomposition leads to a Schur complement system in which the unknowns are the state and adjoint variables on the subdomain interfaces. The Schur complement operator is the sum of subdomain Schur complement operators, the application of which is shown to correspond to the solution of subdomain optimal control problems, which are essentially smaller copies of the original optimal control problem. We show that, under suitable conditions, the application of the inverse of the subdomain Schur complement operators requires the solution of a subdomain elliptic linear-quadratic optimal control problem with Robin boundary conditions for the state. Numerical tests for problems with distributed and with boundary control show that the dependence of the preconditioners on mesh size and subdomain size is comparable to its counterpart applied to a single advection dominated equation. These tests also show that the preconditioners are insensitive to the size of the control regularization parameter.
机译:我们提出了一种优化级域分解(DD)预处理器,以解决对流占主导地位的椭圆线性-二次最优控制问题,该问题在许多科学和工程应用中都会出现。 DD预调节器基于将椭圆线性二次最优控制问题的最优条件分解为较小的子域最优条件,其中子域界面的状态和伴随有Dirichlet边界条件。这些子域最优性条件通过状态和伴随的Robin传输条件耦合。 Robin传输条件中的参数取决于对流。这种分解导致了Schur补码系统,其中未知数是子域接口上的状态和伴随变量。 Schur补算子是子域Schur补算子的总和,其应用表明与子域最优控制问题的解决方案相对应,后者实际上是原始最优控制问题的较小副本。我们表明,在合适的条件下,子域Schur补算子逆的应用要求以状态为Robin的条件求解子域椭圆线性-二次最优控制问题。对具有分布和边界控制问题的数值测试表明,预处理器对网格大小和子域大小的依赖性与应用于单个对流主导方程的类似性相当。这些测试还表明,预处理器对控件正则化参数的大小不敏感。

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