This paper proposes a sensorless cascaded model predictive control strategy applied to a doubly-fed induction machine. This technique is based on an improved stator flux estimator, and an extended Kalman filter to control encoder-less and independently the electromagnetic torque and the reactive power of the machine. The purpose of employing a model predictive-based control, is to achieve fast dynamic response and upgrading it with a modulation stage to mitigate the control variables ripple. The introduced control technique might be considered for adjustable speed application such as wind energy conversion systems. © 2020 IEEE.
Sensorless Cascaded-Model Predictive Control applied to a Doubly Fed Induction Machine
Zanchetta P.
2020-01-01
Abstract
This paper proposes a sensorless cascaded model predictive control strategy applied to a doubly-fed induction machine. This technique is based on an improved stator flux estimator, and an extended Kalman filter to control encoder-less and independently the electromagnetic torque and the reactive power of the machine. The purpose of employing a model predictive-based control, is to achieve fast dynamic response and upgrading it with a modulation stage to mitigate the control variables ripple. The introduced control technique might be considered for adjustable speed application such as wind energy conversion systems. © 2020 IEEE.File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
