Title :
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
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;
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
DOI :
10.1109/ICICISYS.2009.5357828
