Reduced-Order Parameter Estimation for Continuous Systems From Sampled Data

[+] Author and Article Information
C. M. Liaw, C. T. Pan

Department of Electrical Engineering, National Tsing Hua University, Hsinchu, 30043, Taiwan

M. Ouyang

Department of Nuclear Engineering, National Tsing Hua University, Hsinchu, 30043, Taiwan

J. Dyn. Sys., Meas., Control 112(2), 305-308 (Jun 01, 1990) (4 pages) doi:10.1115/1.2896140 History: Received September 01, 1988; Revised January 05, 1989; Online March 17, 2008


An indirect method for estimating the parameters of the reduced continuous-time model from the sampled input/output data is presented. In this method, a discrete-time ARMA model is first identified. Then, the order of the continuous-time model is minimized by the dispersion analysis and/or accumulated dispersion analysis with the criterion of minimum discrepancy in sense of energy contribution between the original system and the reduced model. Finally, the reduced continuous-time model is matched to the identified discrete ARMA model in frequency domain. The proposed approach is applied to the identification of a power system stabilizer. The results show that the estimated continuous-time models are rather close to those supplied by the vender.

Copyright © 1990 by The American Society of Mechanical Engineers
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