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An alternating descent method for the optimal control of the inviscid Burgers equation in the presence of shocks.

机译:一种交替下降法,用于在有冲击的情况下最优控制无粘Burgers方程。

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摘要

We introduce a new optimization strategy to compute numerical approximations of minimizers for optimal control problems governed by scalar conservation laws in the presence of shocks. We focus on the 1 − d inviscid Burgers equation. We first prove the existence of minimizers and, by a -convergence argument, the convergence of discrete minima obtained by means of numerical approximation schemes satisfying the so called onesided Lipschitz condition (OSLC). Then we address the problem of developing efficient descent algorithms. We first consider and compare the existing two possible approaches: the so-called discrete approach, based on a direct computation of gradients in the discrete problem and the so-called continuous one, where the discrete descent direction is obtained as a discrete copy of the continuous one. When optimal solutions have shock discontinuities, both approaches produce highly oscillating minimizing sequences and the effective descent rate is very weak. As a solution we propose a new method, that we shall call alternating descent method, that uses the recent developments of generalized tangent vectors and the linearization around discontinuous solutions. This method distinguishes and alternates the descent directions that move the shock and those that perturb the profile of the solution away of it producing very efficient and fast descent algorithms.
机译:我们引入了一种新的优化策略,可以计算在存在冲击时由标量守恒定律控制的最优控制问题的最小化器的数值逼近。我们关注于1-d无粘性Burgers方程。我们首先证明了极小子的存在,并通过-convergence参数证明了离散极小的收敛,该离散极小是通过满足所谓的Lipschitz条件(OSLC)的数值逼近方案获得的。然后,我们解决了开发有效的下降算法的问题。我们首先考虑并比较现有的两种可能的方法:基于离散问题中梯度的直接计算的所谓离散方法,以及所谓的连续方法,其中连续下降方向是离散下降方向的副本。连续的。当最佳解决方案具有冲击不连续性时,两种方法都会产生高度振荡的最小化序列,并且有效下降率非常弱。作为解决方案,我们提出了一种新的方法,称为交替下降法,该方法利用了广义切向量和不连续解周围线性化的最新发展。该方法区分并交替了使冲击移动的下降方向和使解决方案的轮廓脱离冲击方向的下降方向,从而产生了非常有效且快速的下降算法。

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