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Mesh-independence of semismooth Newton methods for Lavrentiev-regularized state constrained nonlinear optimal control problems

机译:Lavrentiev正规态约束非线性最优控制问题的半光滑牛顿方法的网格独立性

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摘要

A class of nonlinear elliptic optimal control problems with mixed control-state constraints arising, e.g., in Lavrentiev-type regularized state constrained optimal control is considered. Based on its first order necessary optimality conditions, a semismooth Newton method is proposed and its fast local convergence in function space as well as a mesh-independence principle for appropriate discretizations are proved. The paper ends by a numerical verification of the theoretical results including a study of the algorithm in the case of vanishing Lavrentiev-parameter. The latter process is realized numerically by a combination of a nested iteration concept and an extrapolation technique for the state with respect to the Lavrentiev-parameter.
机译:考虑一类具有混合控制状态约束的非线性椭圆最优控制问题,例如在Lavrentiev型正则化状态约束的最优控制中。基于一阶必要最优条件,提出了一种半光滑的牛顿法,证明了其在函数空间中的快速局部收敛性以及适用于离散化的网格无关性原理。本文对理论结果进行了数值验证,包括对Lavrentiev参数消失的算法的研究。后者的过程是通过嵌套迭代概念和关于Lavrentiev参数的状态的外推技术的组合在数值上实现的。

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