Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Kalman filter estimation of RLC parameters for UMP transmission line

View through CrossRef
This paper present the development of Kalman filter that allows evaluation in the estimation of resistance (R), inductance (L), and capacitance (C) values for Universiti Malaysia Pahang (UMP) short transmission line. To overcome the weaknesses of existing system such as power losses in the transmission line, Kalman Filter can be a better solution to estimate the parameters. The aim of this paper is to estimate RLC values by using Kalman filter that in the end can increase the system efficiency in UMP. In this research, matlab simulink model is developed to analyse the UMP short transmission line by considering different noise conditions to reprint certain unknown parameters which are difficult to predict. The data is then used for comparison purposes between calculated and estimated values. The results have illustrated that the Kalman Filter estimate accurately the RLC parameters with less error. The comparison of accuracy between Kalman Filter and Least Square method is also presented to evaluate their performances.
Title: Kalman filter estimation of RLC parameters for UMP transmission line
Description:
This paper present the development of Kalman filter that allows evaluation in the estimation of resistance (R), inductance (L), and capacitance (C) values for Universiti Malaysia Pahang (UMP) short transmission line.
To overcome the weaknesses of existing system such as power losses in the transmission line, Kalman Filter can be a better solution to estimate the parameters.
The aim of this paper is to estimate RLC values by using Kalman filter that in the end can increase the system efficiency in UMP.
In this research, matlab simulink model is developed to analyse the UMP short transmission line by considering different noise conditions to reprint certain unknown parameters which are difficult to predict.
The data is then used for comparison purposes between calculated and estimated values.
The results have illustrated that the Kalman Filter estimate accurately the RLC parameters with less error.
The comparison of accuracy between Kalman Filter and Least Square method is also presented to evaluate their performances.

Related Results

Relevance of rosette patterns in variants of papillary thyroid carcinoma
Relevance of rosette patterns in variants of papillary thyroid carcinoma
AbstractIntroductionThe detection of rosette‐like clusters (RLC) of follicular cells in thyroid carcinoma has been reported mostly in the columnar cell variant of papillary thyroid...
PREDIKSI ARAH DATANG BOLA MENGGUNAKAN KALMAN FILTER PADA ROBOT KIPER SEPAKBOLA
PREDIKSI ARAH DATANG BOLA MENGGUNAKAN KALMAN FILTER PADA ROBOT KIPER SEPAKBOLA
Robot kiper merupakan robot yang bertugas menjaga gawang dari masuknya bola oleh robot tim lawan. Permasalahan yang dihadapi dalam merancang robot kiper adalah bagaimana meningkatk...
State-Space Model and Kalman Filter Gain Identification by a Kalman Filter of a Kalman Filter
State-Space Model and Kalman Filter Gain Identification by a Kalman Filter of a Kalman Filter
This paper describes an algorithm that identifies a state-space model and an associated steady-state Kalman filter gain from noise-corrupted input–output data. The model structure ...
Kalman Filtresi
Kalman Filtresi
Bu kitap, Kalman filtresi konusunu ele almaktadır. Kalman filtresi, bir sistemin durumunu tahmin etmek için kullanılan bir istatistiksel filtreleme yöntemidir. Kitap, kesikli-zaman...
Rocket tracking impact point prediction using α-β, standard Kalman, extended, Kalman, and unscented Kalman filters: a comparative analysis
Rocket tracking impact point prediction using α-β, standard Kalman, extended, Kalman, and unscented Kalman filters: a comparative analysis
Accurate information about the impact point (IP) of a suborbital rocket on Earth’s surface during a launch is an important requirement for range safety operations. Four different e...
Dynamic Models of Satellite Relative Motion and their effects on Kalman Filter
Dynamic Models of Satellite Relative Motion and their effects on Kalman Filter
Abstract In this paper we will study the effects of an increasingly complex Kalman filter state transition matrix on the accuracy of the estimation of a non-linear r...

Back to Top