A memory-efficient model order reduction for time-delay systems

作者：Zhang, Yujie; Su, Yangfeng^*

来源：BIT Numerical Mathematics, 2013, 53(4): 1047-1073.

DOI：10.1007/s10543-013-0439-z

• Krylov subspace
• Compact Arnoldi decomposition
• Two-level orthogonalization Arnoldi process
• Model order reduction
• Moment-matching property

Michiels et al. (SIAM J. Matrix Anal. Appl. 32(4):1399-1421, 2011) proposed a Krylov-based model order reduction (MOR) method for time-delay systems. In this paper, we present an efficient process, which requires less memory consumption, to accomplish the model reduction. Memory efficiency is achieved by replacing the classical Arnoldi process in the MOR method with a two-level orthogonalization Arnoldi (TOAR) process. The resulting memory requirement is reduced from quadratic dependency of the reduced order to linear dependency. Besides, this TOAR process can also be applied to reduce the original delay system into a reduced-order delay system. Numerical experiments are given to illustrate the feasibility and effectiveness of our method.

• 单位
  复旦大学