Normalized-Model Reference System for Parameter Estimation of Induction Motors
Abstract
This manuscript proposes a short tuning march algorithm to estimate induction motors (IM) electrical and mechanical parameters. It has two main novel proposals. First, it starts by presenting a normalized-model reference adaptive system (N-MRAS) that extends a recently proposed normalized model reference adaptive controller for parameter estimation of higher-order nonlinear systems, adding filtering. Second, it proposes persistent exciting (PE) rules for the input amplitude. This N-MRAS normalizes the information vector and identification adaptive law gains for a more straightforward tuning method, avoiding trial and error. Later, two N-MRAS designs consider estimating IM electrical and mechanical parameters. Finally, the proposed algorithm considers starting with a V/f speed control strategy, applying a persistently exciting voltage and frequency, and applying the two designed N-MRAS. Test bench experiments validate the efficacy of the proposed algorithm for a 10 HP IM.
Más información
Título según WOS: | Normalized-Model Reference System for Parameter Estimation of Induction Motors |
Título de la Revista: | ENERGIES |
Volumen: | 15 |
Número: | 13 |
Editorial: | MDPI |
Fecha de publicación: | 2022 |
DOI: |
10.3390/en15134542 |
Notas: | ISI |