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Sensorless and Modulated Model-Predictive Control for a Doubly Fed Induction Machine
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| Author(s) |
Jacopo RICCIO |
| Abstract |
In this paper a sensorless control strategy has been implemented and experimentally validated to control independently the electromagnetic torque and the reactive power of a doubly-fed induction machine. The machine acts as a grid connected generator at variable speed operations around the synchronous speed. This control strategy is based on a model-predictive control strategy with the governing equations represented in a synchronous reference frame aligned to the stator flux. A modulation stage has been introduced in order to overcome the well-known issues of the model-predictive control strategies, such as high current ripple and the non-constant switching frequency. The stator flux vector has been identified by using a programmable low-pass filter achieving an acceptable estimate which is not affected by the integer offset derived problems, and it does not require high number of calculations as by using a full-order observer. The rotor position feedback signal needed to implement the control strategy has been estimated by using an extended Kalman filter. The machine under test is a 7.5kW doubly-fed induction machine. Simulations are carried out by using the software Matlab/Simulink 2018b showing how the electromagnetic torque and the reactive power of the machine can be successfully controlled without the need of the encoder signal; furthermore low current ripple and high dynamic response can be achieved making the studied control strategy suitable for grid-connected variable speed operation such as wind energy conversion systems. |
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| Filename: | 0637-epe2019-full-22415073.pdf |
| Filesize: | 759.2 KB |
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| Type |
Members Only |
| Date |
Last modified 2020-08-14 by System |
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