Parameters estimation for RL electrical circuits based on least square and Bayesian approach

Abstract

Purpose

The main purpose of this paper is to estimate the resistance and inductor in the RL electrical circuit when these are unavailable or missing data that it is a concern in electrical engineering. The input voltage is assumed to be corrupted by the noise and the current is observed at discrete time points.

Design/methodology/approach

The authors propose a computationally efficient framework for parameters estimation using least square estimator and Bayesian Monte Carlo scheme.

Findings

The explicit formulas for least square estimator are derived and the strong consistency of resistance estimator is verified when inductor is a known parameter, then Bayesian estimation of parameters governed by using Markov chain Monte Carlo methods. The applicability of the results is demonstrated by using numerical examples. Several numerical results and figures are presented via Matlab and R programming to illustrate the performance of the estimators.

Practical implications

The paper can be used in various types of electrical engineering real time projects. The projects include electrical circuits, electrical machines theory and drives, especially when the parameters are uncertain that it is a worry in electrical engineering.

Originality/value

To the author's best knowledge, least square and Bayesian estimation of resistance and inductor have not been studied before. The proposed model is nonlinear with respect to inductor (L); therefore the present work has fundamental difference in comparison with the similar models.

Citation

Farnoosh, R., Nabati, P. and Hajirajabi, A. (2012), "Parameters estimation for RL electrical circuits based on least square and Bayesian approach", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 31 No. 6, pp. 1711-1725. https://doi.org/10.1108/03321641211267083