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

Kohei SUZUKI, Koh Kawanobe

Year
1987
Citations
2
Access
Open access

Abstract

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.

Keywords

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

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