首页 /研究 /Dynamic system identification based on two-dimensional autoregressive model fitting.
OTHER

Dynamic system identification based on two-dimensional autoregressive model fitting.

Kohei SUZUKI, Koh Kawanobe

发表年份
1987
引用次数
2
访问权限
开放获取

摘要

This report deals with dynamic system identification which is based on two-dimensional autoregressive (AR) model fitting. The method proposed basically utilizes mapping correspondence between modal parameters shown in a z-transformed plane and those in a Laplacian (s-domain) plane. In order to reduce computer consuming time, the EFFT algorithm by Gan is introduced, and satisfactory time reduction can be obtained. As a practical application of the method, the time-dependent behavior of vibration parameter for the robot arm structure is identified and represented by trajectories in the s-characteristic plane.

关键词

Autoregressive modelModalIdentification (biology)Plane (geometry)Computer scienceAlgorithmSystem identificationAutoregressive–moving-average modelReduction (mathematics)Time domain

相关论文

查看 OTHER 分类全部论文