<abstract xmlns="http://www.w3.org/1999/xhtml"><p>This paper presents predictive speed control of induction motor. The structure with finite control set and long prediction horizon is proposed. In methods with finite set of solutions there is assumed the use of signals that can be obtained in inverter only. Long prediction horizons allow better performance of predictive control structures to be achieved. In this case, long prediction horizon refers to systems with more than one prediction step. The weighting factors determine the properties of control structure via an optimization method using genetic algorithms. The results of simulation studies has been presented.</p></abstract>

This paper presents predictive speed control of induction motor. The structure with finite control set and long prediction horizon is proposed. In methods with finite set of solutions there is assumed the use of signals that can be obtained in inverter only. Long prediction horizons allow better performance of predictive control structures to be achieved. In this case, long prediction horizon refers to systems with more than one prediction step. The weighting factors determine the properties of control structure via an optimization method using genetic algorithms. The results of simulation studies has been presented.

Finite Set Model Predictive Speed Control of Induction Motor with Long Horizon

Power Electronics and Drives

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Finite Set Model Predictive Speed Control of Induction Motor with Long Horizon"}

This paper presents predictive speed control of induction motor. The structure with finite control set and long prediction horizon is proposed. In methods with...

Finite Set Model Predictive Speed Control of Induction Motor with Long Horizon

Pubblicato online: 27 ott 2017

Pagine: 117 - 126

Ricevuto: 23 mar 2016

Accettato: 22 giu 2016

DOI: https://doi.org/10.5277/ped160109

© 2017

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.