Frequency Weighted Model Reduction Based on LMI

DOI

10.2991/icmii-15.2015.32How to use a DOI?

Keywords

model reduction, norm, non-convex optimization, cone complementarity algorithm.

Abstract

This paper treats the problem of a frequency-weighted optimal model reduction problem for linear time-invariant (LTI) systems. An algorithm based on the LMI is derived to solve the frequency weighted model reduction problem. The aim of the algorithm is to minimize norm of the frequency-weighted truncation error between a given LTI system and its lower order approximation. Necessary and sufficient conditions for solving this problem is to meet a series of rank constraints, which generally lead to a non-convex feasibility problem. In addition, it has ensured the stability of reduced-order model when both stable input and output weights are included. Compared with the existing algorithm, the error in this paper is relatively small. An efficient model reduction scheme based on cone complementarity algorithm (CCA) is proposed to solve the non-convex conditions involving rank constraint.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yuan Jiang
AU  - Juan Wu
AU  - Jiyang Dai
PY  - 2015/10
DA  - 2015/10
TI  - Frequency Weighted Model Reduction Based on LMI
BT  - Proceedings of the 3rd International Conference on Mechatronics and Industrial Informatics
PB  - Atlantis Press
SP  - 172
EP  - 178
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmii-15.2015.32
DO  - 10.2991/icmii-15.2015.32
ID  - Jiang2015/10
ER  -