This paper proposes a simple adaptive notch filter for the elimination of the dc component in the integration of signals used for the flux estimation in high performance ac drives. This in- tegration method is composed of two identical adaptive noise can- cellers using a linear neural network with just one bias weight. Its behavior has been investigated in simulation as applied to electrical drives and compared with other four traditional integration algo- rithms. A test bench has been then developed for its experimenta- tion in a field oriented controlled induction machine. It has been verified that this integration algorithm outperforms the other al- gorithms in estimating the rotor flux even at low speeds.

A New Adaptive Integration Methodology for Estimating Flux in Induction Machine Drives

M Pucci;
2004

Abstract

This paper proposes a simple adaptive notch filter for the elimination of the dc component in the integration of signals used for the flux estimation in high performance ac drives. This in- tegration method is composed of two identical adaptive noise can- cellers using a linear neural network with just one bias weight. Its behavior has been investigated in simulation as applied to electrical drives and compared with other four traditional integration algo- rithms. A test bench has been then developed for its experimenta- tion in a field oriented controlled induction machine. It has been verified that this integration algorithm outperforms the other al- gorithms in estimating the rotor flux even at low speeds.
2004
Istituto di Studi sui Sistemi Intelligenti per l'Automazione - ISSIA - Sede Bari
Field oriented control
flux model
induction ma- chine
neural network.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/24478
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