The Effect of ANFIS Controller on The Performance of Induction Motor Drives in Low-Speed Operation Based on IFOC

Era Purwanto, Indra Ferdiansyah, Syechu Dwitya Nugraha, Ony Asrarul Qudsi


The performance of the low-speed operation of induction motor (IM) drives has been discovered to be degrading and the performance of indirect field-oriented control (IFOC)-based IM drives depends on the efficiency of the inner loop Stator Current Regulator (SCR). Therefore, this research proposed the use of the Adaptive Neuro-Fuzzy Inference System (ANFIS) SCR to enhance the performance and optimize the operations of IFOC-based IM drives. It also compared the controller with PI SCR to analyze and evaluate the differences in how they perform. The results showed PI and ANFIS produced the same dynamic speed response trend and the use of ANFIS was able to reduce integral absolute error (IAE) up to 0.481% and phase current consumption from 2.78A – 6.32A both in peak and RMS value. Furthermore, there was a 29.29% - 45.58% reduction in the phase current total harmonic distortion (THD). This means the application of ANFIS SCR on IFOC-based IM drives enhanced the performance in the current constraint for high-performance purposes and low-speed applications.


IFOC; low-speed operation; stator current regulator; ANFIS.

Full Text:



Ferdiansyah, I.; Rusli,M.R.; Praharsena,B.;Toar,H.; Ridwan; and Purwanto,E.(2018). Speed Control of Three Phase Induction Motor Using Indirect Field Oriented Control Based on Real-Time Control System. Proceedings of2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE). Kuta,438-442.

Praharsena,B.; Purwanto,E.; Jaya,A.; Rusli, M.R.; Toar, H.; and Ridwan(2018). Stator Flux Estimator Using Feed-Forward Neural Network for Evaluating Hysteresis Loss Curve in Three Phase Induction Motor.EMITTER International Journal of Engineering Technology,6(1), 168-184.

Praharsena,B.; and et al.(2018). Evaluation of Hysteresis Loss Curve on 3 Phase Induction Motor by Using Cascade Feed Forward Neural Network.Proceedings of2018 International Electronics Symposium on Engineering Technology and Applications (IES-ETA). Bali, 117-122.

Bennassar, A.; Abbou, A.; Akherraz, M.;and Barara, M.(2016). "Fuzzy Logic Based Adaptation Mechanism for Adaptive Luenberger Observer Sensorless Direct Torque Control Of Induction Motor." Journal of Engineering Science and Technology (JESTEC),11(1), 46-59.

Hannan, M.A.;Ali, J.A.;Mohamed, A.; and Hussain, A. (2018).Optimization techniques to enhance the performance of induction motor drives: A review.Renewable and Sustainable Energy Reviews,81(2), 1611-1626.

Zhang, B.; Liang, B.; Xu, G.; Wang, W.; and Feng, G. (2011). Research on variable frequency low-speed high-torque squirrel cage induction machine for elevator. Proceedings of 2011 International Conference on Electrical Machines and Systems.Beijing, 1-5.

Munoz-Garcia, A.; Lipo, T.A.; and Novotny, D.W. (1998). A new induction motor V/f control method capable of high-performance regulation at low speeds.IEEE Transactions on Industry Applications,34(4), 813-821.

Lee, D.-C.; Sul, S.-K.; and Park, M.-H. (1994). High performance current regulator for a field-oriented controlled induction motor drive.IEEE Transactions on Industry Application,30(5), 1247-1257.

Briz, F.; Diez, A.; Degner, M.W.; and Lorenz, R.D. (2001). Current and flux regulation in field-weakening operation [of induction motors]. IEEE Transactions on Industry Applications,37(1), 42-50.

Quang, N.P.;and Dittrich, J.-A. (2015). Vector Control of Three-Phase AC Machines.Heidelberg:Springer-Verlag Berlin.

Rashid, M. (2017). Power Electronics Handbook (Fourth Edition). Saint Louis: Butterworth-Heinemann.

Krishnan, R. (2001). Electric Motor Drives: Modeling, Analysis, and Control.Prentice Hall.

Hannan, M.A.; Ali, J.A.; Mohamed A.; Amirulddin, U.A.U.; Tan,N.M.L.; and Uddin, M.N.(2018). Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for IM Drive. IEEE Transactions on Industry Applications,54(4), 3793-3805.

Ali, J.A.; Hannan, M.A.; and Mohamed, A. (2016). Improved Indirect Field-Oriented Control of Induction Motor Drive Based PSO Algorithm. Jurnal Teknologi,78(6-2), 27-32.

Aditya, A.W.; Happyanto, D.C.; and Sumantri, B. (2017). Application of Sliding Mode Control in Indirect Field Oriented Control (IFOC) for Model Based Controller. EMITTER International Journal of Engineering Technology,5(2), 255-269.

Aditya, A.W.; Rusli, M.R.; Praharsena, B.; Purwanto, E.; Happyanto, D.C.; and Sumantri, B. (2018). The Performance of FOSMC and Boundary - SMC in Speed Controller and Current Regulator for IFOC-Based Induction Motor Drive.Proceedings of 2018 International Seminar on Application for Technology of Information and Communication.Semarang, 139-144.

Talib, M.H.N.; Ibrahim, Z.; Rasin, Z.; Lazi, J.M.;and Azri, M. (2017). Investigation of Different Rules Size FLSC Performance Applied to Induction Motor Drive. Journal of Telecommunication, Electronic and Computer Engineering,9(2-8),165-169.

Salleh, Z.; Sulaiman, M.; and Omar, R. (2016). Tuning Fuzzy Membership Functions to Improve Performance of Vector Control Induction Motor Drives.Journal of Telecommunication, Electronic and Computer Engineering,8(2), 1-4.

Azcue-Puma, J.L.; Sguarezi Filho,A.J.; and Ruppert, E.(2013). Direct-FOC with Fuzzy Current Control for asynchronous machine. Proceedings of 2013 IEEE International Conference on Industrial Technology (ICIT). Cape Town, 307-312

El-Sousy, F.F.M.; and Nashed, M.N.F. (2003). Robust Fuzzy Logic Current and Speed Controllers for Field-Oriented Induction Motor Drive. Journal of Power Electronics,3(2), 115-123.

Boussada, Z.; Hamed, M.B.; and Sbita, L.(2014). Adaptive neuro-fuzzy inference system into induction motor: Estimation.Proceedings of 2014 International Conference on Electrical Sciences and Technologies in Maghreb (CISTEM). Tunis, 1-5.

Kılıç, E.; Yılmaz, Ş.; Özçalık, H.R.; and Şit, S. (2000). A comparative analysis of FLC and ANFIS controller for vector controlled induction motor drive.Proceedings of 2015 Intl Aegean Conference on Electrical Machines & Power Electronics (ACEMP), 2015 Intl Conference on Optimization of Electrical & Electronic Equipment (OPTIM) & 2015 Intl Symposium on Advanced Electromechanical Motion Systems (ELECTROMOTION).Side, 102-106.

Mechernene, A.; Zerikat, M.; and Chekroun, S. (2010). Indirect field oriented adaptive control of induction motor based on neuro-fuzzy controller. Proceedings of 18th Mediterranean Conference on Control and Automation.Marrakech, 1109-1114.

Mishra, R.N.; and Mohanty, K.B. (2016). Real time implementation of an ANFIS-based induction motor drive via feedback linearization. Engineering Science and Technology, an International Journal,19(4), 1714-1730.

Hussain,S.; and Bazaz, M.A.(2014). ANFIS implementation on a three phase vector controlled induction motor with efficiency optimisation.Proceedings of 2014 International Conference on Circuits, Systems, Communication and Information Technology Applications (CSCITA).Mumbai, 391-396.

Nour, M.; and Too, S.Y. (2006). Adaptive Fuzzy Logic Speed Controller With Torque Adapted Gains Function for PMSM Drive.Journal of Engineering Science and Technology (JESTEC),1(1), 59-75.

Gupta, R.A.; Kumar, R.; and Surjuse, R.S. (2009). ANFIS Based Intelligent Control of Vector Controlled Induction Motor Drive.Proceedings of 2009 Second International Conference on Emerging Trends in Engineering & Technology.Nagpur, 674-680.

Duarte-Mermoud, M.A.; and Prieto, R.A. (2004). Performance index for quality response of dynamical systems. ISA Transactions,43, 133-151.



  • There are currently no refbacks.

Published by INSIGHT - Indonesian Society for Knowledge and Human Development