Model order reduction for control systems
Báo cáo viên: Chu Bình Minh

Thời gian: 9h30, Thứ 3, ngày 9/4/2019

Địa điểm: Phòng 302, Nhà A5, Viện Toán học

Tóm tắt: Designing a control system for complex models leads to very large scale problems which require huge computing resources. Model order reduction is a technique to approximate these very large systems by simpler ones of appropriate order but keeping their most important features. In this talk we present some model order reduction for

  1. Stable symmetric linear state-space systems,
  2. Unstable linear state-space systems

and the balanced generalized singular perturbation method for unstable linear time invariant continuous systems.

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