Model order reduction for optimality systems through empirical gramians

被引:0
作者
Mechelli, Luca [1 ]
Rohleff, Jan [1 ]
Volkwein, Stefan [1 ]
机构
[1] Univ Konstanz, Dept Math & Stat, Constance, Germany
关键词
model order reduction; empirical gramians; proper orthogonal decomposition; parabolic partial differential equations; multiobjective optimization; model predictive control; a-posteriori error analysis; EQUATIONS;
D O I
10.3389/fams.2023.1144142
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
In the present article, optimal control problems for linear parabolic partial differential equations (PDEs) with time-dependent coefficient functions are considered. One of the common approach in literature is to derive the first-order sufficient optimality system and to apply a finite element (FE) discretization. This leads to a specific linear but high-dimensional time variant (LTV) dynamical system. To reduce the size of the LTV system, we apply a tailored reduced order modeling technique based on empirical gramians and derived directly from the first-order optimality system. For testing purpose, we focus on two specific examples: a multiobjective optimization and a closed-loop optimal control problem. Our proposed methodology results to be better performing than a standard proper orthogonal decomposition (POD) approach for the above mentioned examples.
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页数:15
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