A novel distance protection algorithm in frequency domain based on parameter identification

2012 ◽  
Author(s):  
J.L. Suonan ◽  
Y. Zhong ◽  
G.B. Song
Keyword(s):  
Parameter Identification ◽  
Frequency Domain ◽  
Distance Protection

Fourier Series-Based Neural Networks for Vehicle System Identification

1999 ◽  
Author(s):  
Imtiaz Haque ◽  
Juergen Schuller
Keyword(s):  
Neural Networks ◽  
Fourier Series ◽  
System Identification ◽  
Transfer Function ◽  
Parameter Identification ◽  
Frequency Domain ◽  
Vehicle System ◽  
Non Linear ◽  
Function Identification ◽  
Non Linear System

Abstract The use of neural networks in system identification is an emerging field. Neural networks have become popular in recent years as a means to identify linear and non-linear systems whose characteristics are unknown. The success of sigmoidal networks in parameter identification has been limited. However, harmonic activation-based neural networks, recent arrivals in the field of neural networks, have shown excellent promise in linear and non-linear system parameter identification. They have been shown to have excellent generalization capability, computational parallelism, absence of local minima, and good convergence properties. They can be used in the time and frequency domain. This paper presents the application of a special class of such networks, namely Fourier Series neural networks (FSNN) to vehicle system identification. In this paper, the applications of the FSNNs are limited to the frequency domain. Two examples are presented. The results of the identification are based on simulation data. The first example demonstrates the transfer function identification of a two-degree-of freedom lateral dynamics model of an automobile. The second example involves transfer function identification for a quarter car model. The network set-up for such identification is described. The results of the network identification are compared with theory. The results indicate excellent prediction properties of such networks.

Structural Parameter Identification in the Frequency Domain: The Use of Overdetermined Systems

1987 ◽  
Vol 109 (2) ◽  
pp. 120-123 ◽  
Author(s):  
S. G. Braun ◽  
Y. M. Ram
Keyword(s):  
Transfer Function ◽  
Parameter Identification ◽  
Frequency Domain ◽  
Rational Function ◽  
Least Square ◽  
Structural Parameter ◽  
Overdetermined Systems ◽  
The Matrix ◽  
Domain Transfer

This paper deals with the fitting of a rational function to an experimentally determined frequency domain transfer function. Examples show that the use of overdetermined fitted systems improve the identification in noisy situations. A method is presented, enabling the determination of the number of zero/poles of the system, and the relation to the rank of the matrix used in a least square identification method.

scholarly journals Parameter Identification of Weakly Nonlinear Vibration System in Frequency Domain

2004 ◽  
Vol 11 (5-6) ◽  
pp. 685-692 ◽  
Author(s):  
Jiehua Peng ◽  
Jiashi Tang ◽  
Zili Chen
Keyword(s):  
Parameter Identification ◽  
Frequency Response ◽  
Nonlinear Vibration ◽  
Frequency Domain ◽  
Response Function ◽  
Frequency Response Function ◽  
Physical Parameters ◽  
Vibration System ◽  
Weakly Nonlinear ◽  
Nonlinear Vibration System

A new method of identifying parameters of nonlinearly vibrating system in frequency domain is presented in this paper. The problems of parameter identification of the nonlinear dynamic system with nonlinear elastic force or nonlinear damping force are discussed. In the method, the mathematic model of parameter identification is frequency response function. Firstly, by means of perturbation method the frequency response function of weakly nonlinear vibration system is derived. Next, a parameter transformation is made and the frequency response function becomes a linear function of the new parameters. Then, based on this function and with the least square method, physical parameters of the system are identified. Finally, the applicability of the proposed technique is confirmed by numerical simulation.

scholarly journals Frequency-domain modeling of unshielded multiconductor power cables for periodic excitation with new experimental protocol for wide band parameter identification

2019 ◽  
Vol 101 (2) ◽  
pp. 333-343 ◽  
Author(s):  
Tamiris G. Bade ◽  
James Roudet ◽  
Jean-Michel Guichon ◽  
Carlos A. F. Sartori ◽  
Patrick Kuo-Peng ◽  
...  
Keyword(s):  
Parameter Identification ◽  
Frequency Domain ◽  
Wide Band ◽  
Domain Modeling ◽  
Power Cables ◽  
Periodic Excitation ◽  
Experimental Protocol ◽  
Band Parameter
Sign in / Sign up

Export Citation Format

Share Document