Normalized-Model Reference System for Parameter Estimation of Induction Motors

Veliz-Tejo, Adolfo; Travieso-Torres, Juan Carlos; Peters, Andres A.; Mora, Andres; Leiva-Silva, Felipe

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: ID WOS:000825676800001 Not found in local WOS DB
Título de la Revista: ENERGIES
Volumen: 15
Número: 13
Editorial: MDPI
Fecha de publicación: 2022
DOI:

10.3390/en15134542

Notas: ISI