Continuous set nonlinear model predictive control for an induction motor

Saeid Saeidi, Ralph Kennel

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

An algorithm for Continuous Set Nonlinear Model Predictive Control (CS-NMPC) is investigated. The proposed strategy is employed to realize flux and torque control for an Induction Motor (IM). It is implemented on an FPGA-based system and its effectiveness is demonstrated with experimental results. The iteration based structure of the algorithm, makes it possible to reduce the needed logic resources. Computational performance of the FPGA implementation is enhanced through a pipelined parallel architecture. A comparison of computation performance shows that, the proposed hardware realization decreases the execution time of CS-NMPC algorithm. The paper concludes with some comments on extension of CS-NMPC to other motor drive types and converter topologies.

Original languageEnglish
Title of host publication2013 15th European Conference on Power Electronics and Applications, EPE 2013
DOIs
StatePublished - 2013
Event2013 15th European Conference on Power Electronics and Applications, EPE 2013 - Lille, France
Duration: 2 Sep 20136 Sep 2013

Publication series

Name2013 15th European Conference on Power Electronics and Applications, EPE 2013

Conference

Conference2013 15th European Conference on Power Electronics and Applications, EPE 2013
Country/TerritoryFrance
CityLille
Period2/09/136/09/13

Keywords

  • Control of drive
  • Field Programmable Gate Array (FPGA)
  • Induction Motor
  • Model Predictive Control (MPC)
  • Non-linear control
  • Voltage Source Inverters (VSI)

Fingerprint

Dive into the research topics of 'Continuous set nonlinear model predictive control for an induction motor'. Together they form a unique fingerprint.

Cite this