2020高端外专系列学术报告通知
Topic: Balanced Truncation Model Reduction with A Priori Error Bounds for LTI Systems with Nonzero Initial Value
Speaker: Prof. Matthias Voigt (University of Hamburg)
Abstract:
In standard balanced truncation model order reduction, the initial condition is typically ignored in the reduction procedure and is assumed to be zero instead. However, such a reduced-order model may be a bad approximation to the full-order system, if the initial condition is not zero. In the literature there are several attempts for modified reduction methods at the price of having no error bound or only a posteriori error bounds which are often too expensive to evaluate. In this talk we propose a new balancing procedure that is based on a shift transformation on the state. We first derive a joint projection reduced-order model in which the part of the system depending only on the input and the one depending only on the initial value are reduced at once and we prove an a priori error bound. With this result at hand, we derive a separate projection procedure in which the two parts are reduced separately. This gives the freedom to choose different reduction orders for the different subsystems. Moreover, we discuss how the reduced-order models can be constructed in practice. Since the error bounds are parameter-dependent we show how they can be optimized efficiently. We conclude this talk by comparing our results with the ones from the literature by a series of numerical experiments.
Arrangement:
Time: 15:00- 16:00, Wednesday, 30st, September
How to join:
Offline: 公司宝山校区东区机自大楼702B会议室
Online: 1) Tencent Meeting & VooV Meeting [腾讯会议]
https://meeting.tencent.com/s/qFK6stCpYSRK
ID：976 664 361
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(二维码有效期：2020-09-29)
资助来源：公司国际部海外引智专项 & 公司国际部海外课程学习项目
国家外专局“111引智基地”（复杂网络化系统智能测控及应用学科创新引智基地）
