Analysis And Investigation Of Different Advanced Control Strategies For High-Performance Induction Motor Drives

Yahya Farah, Nabil Salem and Talib, Md Hairul Nizam and Ibrahim, Zulkifilie and Abdullah, Qazwan and Aydoğdu, Ömer and Rasin, Zulhani and Jidin, Auzani and Mat Lazi, Jurifa (2020) Analysis And Investigation Of Different Advanced Control Strategies For High-Performance Induction Motor Drives. Telkomnika (Telecommunication Computing Electronics and Control), 18 (6). pp. 3303-3314. ISSN 1693-6930

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Abstract

Induction motor (IM) drives have received a strong interest from researchers and industry particularly for high-performance AC drives through vector control method. With the advancement in power electronics and digital signal processing (DSP), high capability processors allow the implementation of advanced control techniques for motor drives such as model predictive control (MPC). In this paper, design, analysis and investigation of two different MPC techniques applied to IM drives; the model predictive torque control (MPTC) and model predictive current control (MPCC) are presented. The two techniques are designed in Matlab/Simulink environment and compared in term of operation in different operating conditions. Moreover, a comparison of these techniques with field-oriented control (FOC) and direct torque control (DTC) is conducted based on simulation studies with PI speed controller for all control techniques. Based on the analysis, the MPC techniques demonstrates a better result compared with the FOC and DTC in terms of speed, torque and current responses in transient and steady-state conditions.

Item Type:	Article
Uncontrolled Keywords:	Current prediction, Flux estimation, Induction motor drives, Model predictive control, Model predictive current control, Model predictive torque control, Predictive control, Torque prediction, High-Performance Induction Motor
Divisions:	Faculty of Electrical Engineering
Depositing User:	Sabariah Ismail
Date Deposited:	10 Dec 2020 11:39
Last Modified:	10 Dec 2020 11:42
URI:	http://eprints.utem.edu.my/id/eprint/24834
Statistic Details:	View Download Statistic

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