MRAS based real-time speed-sensorless control of induction motor with optimized fuzzy-PI controller

In this paper, rotor flux-oriented model reference adaptive system (RF-MRAS) based estimators are designed to obtain flux and speed estimations for speed-sensorless control of induction motors (IMs). The proposed RF-MRAS in this work replaces Conventional PI controller (CPI) in adaptation mechanism of RF-MRAS with fuzzy-PI (FPI) controller in order to improve conventional RF-MRAS. Additionally, the gains of both FPI and CPI controllers are optimized by offline via differential evolution algorithm (DEA) to make fair comparisons and without using time-consuming process of trial-and-error method.

[1]  山川 烈,et al.  Soft Computing , 2000, Soft Comput..

[3]  C. Schauder,et al.  Adaptive speed identification for vector control of induction motors without rotational transducers , 1989, Conference Record of the IEEE Industry Applications Society Annual Meeting,.

[4]  Murat Barut,et al.  Experimental Evaluation of Braided EKF for Sensorless Control of Induction Motors , 2008, IEEE Transactions on Industrial Electronics.

[5]  Murat Barut,et al.  Optimization of Model Reference Adaptive System Based Speed Estimation for Speed-Sensorless Control of Induction Motors Via Differential Evolution Algorithm , 2013, ALCOSP.

[6]  Ali Keyhani,et al.  A comparative study of rotor flux based MRAS and back EMF based MRAS speed estimators for speed sensorless vector control of induction machines , 1997, IAS '97. Conference Record of the 1997 IEEE Industry Applications Conference Thirty-Second IAS Annual Meeting.

[7]  Bimal K. Bose.  High performance control and estimation in AC drives , 1997, Proceedings of the IECON'97 23rd International Conference on Industrial Electronics, Control, and Instrumentation (Cat. No.97CH36066).

[8]  Damian Giaouris,et al.  MRAS Sensorless Vector Control of an Induction Motor Using New Sliding-Mode and Fuzzy-Logic Adaptation Mechanisms , 2010, IEEE Transactions on Energy Conversion.

[9]  N. Salvatore,et al.  Differential evolution optimization of DSKF algorithm for sensorless SFO control of IM drives , 2008, 2008 34th Annual Conference of IEEE Industrial Electronics.

[10]  Ferrante Neri,et al.  Optimization of Delayed-State Kalman-Filter-Based Algorithm via Differential Evolution for Sensorless Control of Induction Motors , 2010, IEEE Transactions on Industrial Electronics.