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.
Reduced-Order Parameter Estimation for Continuous Systems From Sampled Data
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Liaw, C. M., Ouyang, M., and Pan, C. T. (June 1, 1990). "Reduced-Order Parameter Estimation for Continuous Systems From Sampled Data." ASME. J. Dyn. Sys., Meas., Control. June 1990; 112(2): 305–308. https://doi.org/10.1115/1.2896140
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