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

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.
9781728158266
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11571/1372964
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