Neurofuzzified Analysis on Torque Control of a Squirrel Cage Induction Machine

Emmanuel Osundina; Peter Daffin Onwe; Eluebo Emmanuel Chuka; Ajoke Alice Awominure; Tosin Tunde Oyetayo

doi:10.59535/jece.v2i1.228

Authors

Emmanuel Osundina University of Calabar
Peter Daffin Onwe University of Calabar
Eluebo Emmanuel Chuka University of Calabar
Ajoke Alice Awominure University of Calabar
Tosin Tunde Oyetayo Osun state University

DOI:

https://doi.org/10.59535/jece.v2i1.228

Keywords:

Direct torque control (DTC), Neural Network (NN), Fuzzy Logic Control (FLC), Induction Motor (IM).

Abstract

The direct torque controller (DTC) is an interesting control scheme for induction motor control. It is suitable for variable-frequency drives for torque and its consequent speed control, specifically for the calculation of the estimated Induction motor's magnetic flux and torque based on the motor's measured voltage and current. However, this scheme has a disadvantage in its implementation that makes it unsuitable for high torque applications, resulting in poor drive parameter variation, optimization, and dynamic responses when compared to field-oriented control (FOC). Fuzzy-based DTC is introduced to control. The high torque ripple nature of the direct torque-controlled induction motor improves drive performance to parameter variation, and improve transient response to step changes in torque during start-up. The neurofuzzy analysis on torque performance under load disturbance shows a transient response and a low step ripple effect. Thus, this improved scheme is recommended for a high inertia application. Such as flywheel presses and rock crushes.

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References

A.V. Buja, G.S. Menis, (2004) ‘Band-constrained technique for direct torque control of induction motor’, IEEE Trans. Ind. Electron., 2004, 51, (4), pp. 776–784

H. Joseph, (2013). Comparative Study of Indirect Vector Control and Direct Torque Control of Induction Motor. International Journal of Technology and Engineering Science (IJTES) Vol. 1(6), pp: 1014-1020, Sept 2013.

B. J. Verveckken, J. Driesen, (2010) ‘Predictive direct torque control for flux and torque ripple reduction’, IEEE Trans. Ind. Electron., 2010, 57, (1), pp. 404–412

C.S. Babu, (2018). A modified multiband hysteresis controlled DTC of induction machine with 27-level asymmetrical CHB-MLI with NVC modulation. Ain Shams Engineering Journal, 9, 15–29.

M. Hoo, E. C. S. Hairi, M. H. B.Salim and I.W.A. Razak, (2015). Comparison of Fuzzy Control Rules using MATLAB Toolbox and Simulink for DC Induction Motor-Speed Control. International Conference of Soft Computing and Pattern Recognition.

B. M. Buja, G. Menis, (2006) ‘Direct torque control of an induction motor using a single current sensor’, IEEE Trans. Ind. Electron., 2006, 53, (3), pp. 778–784

A. Thevin, (2019). Modified vector controlled DFIG wind energy system based on barrier function adaptive sliding mode control. Protection and Control of Modern Power Systems, 4(1),

J.A. Olaniyi, O.M. Folorunso and O.T Arulogun,(2019). Poultry Feed Dispensing System Control: A Case between Fuzzy Logic Controller and PID Controller. Balkan Journal of Electrical & Computer Engineering, 7(2), April 2019

G.P. Dhok, (2018), ANFIS control scheme for the speed control of the induction motor.

C. M. Jebin and P.K. Prathibha, (2017). Comparison of PI, PID Controller and Fuzzy PI Controller for BLDC Speed Control Application, Department of Electrical & Electronics Engineering. International Journal for Scientific Research & Development| Vol. 5, Issue 09, 2017 | ISSN (online): 2321-0613.

C.L. Graciola, B.A. Angélico, A, Goedtel and M.F. Castoldi, (2018). Metaheuristics optimization applied to PI controllers tuning of a DTC-SVM drive for three-phase induction motors. Applied Soft Computing, 62, 776–788.

S.P. Dhongade and K.B. Porate, (2016). Slip Energy Recovery of Induction Motor using Converter. Department of Electrical Engineering PCE Nagpur.

A. Didem, (2019). Performance Comparison of Fuzzy Logic and PID Controller for Speed Control of DC Motor in Distribution Grid. International Research Journal of Engineering and Technology (IRJET). E-ISSN: 2395-0056. P-ISSN: 2395-0072. Vol. 06 Issue: 02 | Feb 2019.

T. Dongale, S.R. Jadhav, S.V. Kulkarni, T.G. Kulkarni, R. R. Mudholkar and U.D. Uplane, (2016). Performance Comparison of PID and Fuzzy Control Techniques in Three Phase Induction Motor Control: Int. J. on Recent Trends in Engineering and Technology, Vol. 7, No. 2, March 2016 Department of Electronics, Shivaji University, Kolhapur, India.

E. Ouanjli, N. Derouich, A. El Ghzizal, A. Chebabhi, A. Taoussi and B. Bossoufi, (2018). Direct torque control strategy based on fuzzy logic controller for a doubly fed induction motor. In IOP conference series: Earth and environmental science (Vol. 161, No. 1, p. 012004). IOP Publishing.

E. Saadawi and A. Hatata, (2017). A novel protection scheme for synchronous generator stator windings based on SVM. Protection and Control of Modern Power Systems, 2(1), 24.

S. S. Hakami, I. Mohd Alsofyani and K.B. Lee, (2020). Low-speed performance improvement of direct torque control for induction motor drives fed by three-level NPC inverter. Electronics, 9(1), 77.

M. Hamouda and L. Számel, (2019). Optimum control parameters of switched reluctance motor for torque production improvement over the entire speed range. Acta Polytechnica Hungarica, 16(3), 79-99.

B. Ishan and S. Bhupender, (2017). Modeling and Simulation for Transformer Ratio Controlled Slip Power Recovery Scheme. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056, Vol: 04 Issue: 07 | July -2017, p-ISSN: 2395-0072.

Y. Jae-Sung, K. Byoung and H. Ying, (2016). Fuzzy-Logic-Based Vector Control Scheme. IEEE Transactions on Industrial Electronics 54(4):2190 - 2200 · September 2007 with 155 Reads DOI: 10.1109/TIE.2007.894692 · Source.

G. Swati and R. Rohini A, (2014). Slip Power recovery system in Three Phase Slip Ring Induction motor. KIIT University Bhubaneswar, India, Electrical Department. IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE) e-ISSN: 2278-1676, p-ISSN: 2320-3331 PP 43-46.

M. Jakel and F. Kelvin, (2018). Design and simulation SERD using fuzzy logic controller Published 2018 in IEEE Trans. Industrial Electronics.