Online parameters identification of low- frequency oscillation by neural computation

Author

Chengcheng, Li ; Fangzong, Wang

Author_Institution

Coll. of Electr. Eng. & Inf. Technol., China Three Gorges Univ., Yichang, China

Volume

1

fYear

2009

fDate

20-22 Nov. 2009

Firstpage

352

Lastpage

356

Abstract

In this paper, we introduce a novel information criterion (NIC) algorithm for online parameter identification of low-frequency oscillation by neural computation. This algorithm can get oscillation frequency, attenuation, amplitude and phase of the system from the data being measured and solve the problem that the rank of the signal covariance matrix is often unknown. Simulation results demonstrate that this algorithm has high resolving power and is time saving.

Keywords

matrix algebra; neural nets; parameter estimation; low-frequency oscillation; neural computation; novel information criterion algorithm; online parameters identification; signal covariance matrix; Attenuation measurement; Covariance matrix; Difference equations; Educational institutions; Eigenvalues and eigenfunctions; Frequency measurement; Information technology; Parameter estimation; Phase measurement; Power engineering computing; NIC algorithm; low-frequency oscillation; neural computation; prony algorithm; rank;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-4754-1

Electronic_ISBN

978-1-4244-4738-1

Type

conf

DOI

10.1109/ICICISYS.2009.5357828

Filename

5357828