Abstract
The paper describes a fuzzy speed controller with direct torque control for induction motor drive. Classical PI speed controller with fixed proportional and integral coefficients is not appropriate for exact motor speed regulation in a wide range of reference speed. Fuzzy logic, one of simplest soft computing techniques, can make PI controllers more flexible. In the paper, a simple fuzzy algorithm is proposed for online update coefficients of PI speed controller. The use of a pulse-width modulator in the direct torque control structure is to ensure the constant switching frequency. The control structures of the induction motor drive are implemented into a control system with digital signal processor. Experimental results confirm that speed controller with proposed fuzzy algorithm gives response of actual motor speed with lower overshoot, shorter settling time, and smaller speed accuracy than classical speed controller does.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Leonhard, W.: Control of Electrical Drives. Springer, Berlin (2001). ISBN 3-540-41820-2
Bose, B.K.: Modern Power Electronics and AC Drives, Prentice Hall, Knoxville (2002). ISBN 0-130-16743-6
Gadoue, S.M., Giaouris, D., Finch, J.W.: Sensorless control of induction motor drives at very low and zero speeds using neural network flux observers. IEEE Trans. Industr. Electron. 56(8), 3029–3039 (2009)
Brandstetter, P., Chlebis, P., Palacky, P., Skuta, O.: Application of RBF network in rotor time constant adaptation. Elektronika ir Elektrotechnika 113(7), 21–26 (2011)
Maiti, S., Verma, V., Chakraborty, C., Hori, Y.: An adaptive speed sensorless induction motor drive with artificial neural network for stability enhancement. IEEE Trans. Industr. Inf. 8(4), 757–766 (2012)
Palacky, P., Hudecek, P., Havel, A.: Real-time estimation of induction motor parameters based on the genetic algorithm. In: The International Joint Conference CISIS 2012-ICEUTE 2012-SOCO 2012 Special Sessions, Advances in Intelligent Systems and Computing, vol. 189, pp. 401–409 (2013)
Costa, B.L.G., Angélico, B.A., Goedtel, A., Castoldi, M.F., Graciola, C.L.: Differential evolution applied to DTC drive for three-phase induction motors using an adaptive state observer. J. Control Autom. Electr. Syst. 26(4), 403–420 (2015)
Laamari, Y., Chafaa, K., Athamena, B.: Particle swarm optimization of an extended Kalman filter for speed and rotor flux estimation of an induction motor. Electr. Eng. 97(2), 129–138 (2015)
Kouzi, K., Nait-Said, M.S., Hilairet, M., Berthlot, E.: Fuzzy MRAS speed estimator for vector control of an induction motor. Int. Rev. Electr. Eng. (IREE) 4(2), 278–283 (2009)
Birou, I., Maie, V., Pavel, S., Rusu, C.: Indirect vector control of an induction motor with fuzzy-logic based speed controller. Adv. Electr. Comput. Eng. 10(1), 116–120 (2010)
Abdalla, T.Y., Hairik, H.A., Dakhil, A.M.: Direct torque control system for a three phase induction motor with fuzzy logic based speed controller. In: The 1st International Conference on Energy, Power and Control (EPC-IQ), Basrah, Iraq, pp. 131–138 (2010)
Brandstetter, P., Friedrich, J., Stepanec, L.: Implementation of fuzzy speed controller in control structure of A.C. drive with induction motor. In: The International Joint Conference CISIS 2013-ICEUTE 2013-SOCO 2013 Special Sessions, Advances in Intelligent Systems and Computing, vol. 239, pp. 379–388 (2014)
Rahmani, R., Langeroudi, N.M.A., Yousefi, R., Mahdian, M., Seyedmahmoudian, M.: Fuzzy logic controller and cascade inverter for direct torque control of IM. Neural Comput. Appl. 25(3), 879–888 (2014)
Chang, Hong-Chan, Lin, Shang-Chih, Kuo, Cheng-Chien, Hsieh, Cheng-Fu: Induction motor diagnostic system based on electrical detection method and fuzzy algorithm. Int. J. Fuzzy Syst. 18(5), 732–740 (2016)
Riad, T., Hocine, B., Salima, M.: New direct torque neuro-fuzzy control based SVM-three level inverter-fed induction motor. Int. J. Control Autom. Syst. 8(2), 425–432 (2010)
Brandstetter, P., Kuchar, M., Vo, H.H., Dong, C.S.T.: Induction motor drive with PWM direct torque control. In: 18th International Scientific Conference on Electric Power Engineering (EPE), Kouty nad Desnou, Czech Republic, pp. 1–5 (2017)
Kumar, B.S., Gupta, R.A., Kumar, R.: 12-sector methodology of torque ripple reduction in a direct torque controlled induction motor drive. In: SICE-ICASE International Joint Conference, pp. 3587–3592 (2006)
Hartani, K., Miloud, Y.: Control strategy for three phase voltage source PWM rectifier based on the space vector modulation. Adv. Electr. Comput. Eng. 10(3), 61–65 (2010)
Cirstea, M.N., Dinu, A., Khor, J.G., McCormick, M.: Neural and Fuzzy Logic Control of Drives and Power Systems. Newnes, Jordan Hill (2002). ISBN 0-750-65558-5
Nguyen, H.T., Prasad, N.R., Walker, C.L., Walker, E.A.: A First Course in Fuzzy and Neural Control, CRC Press, Boca Raton (2003). ISBN 1-584-88244-1
Vo, H.H., Brandstetter, P., Dong, C.S.T., Tran, T.C.: Speed estimators using stator resistance adaptation for sensorless induction motor drive. Adv. Electr. Electron. Eng. 14(3), 267–273 (2016)
Acknowledgement
The paper was supported by the projects: Center for Intelligent Drives and Advanced Machine Control (CIDAM) project, reg. no. TE02000103 funded by the Technology Agency of the Czech Republic, project reg. no. SP2017/104 funded by the Student Grant Competition of VSB-Technical University of Ostrava.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Vo, H.H., Brandstetter, P., Kuchar, M., Dong, C.S.T., Tran, T.C., Vo, D.H. (2018). PI-Based Fuzzy Speed Controller with PWM Direct Torque Control for Induction Motor Drive. In: Duy, V., Dao, T., Zelinka, I., Kim, S., Phuong, T. (eds) AETA 2017 - Recent Advances in Electrical Engineering and Related Sciences: Theory and Application. AETA 2017. Lecture Notes in Electrical Engineering, vol 465. Springer, Cham. https://doi.org/10.1007/978-3-319-69814-4_78
Download citation
DOI: https://doi.org/10.1007/978-3-319-69814-4_78
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-69813-7
Online ISBN: 978-3-319-69814-4
eBook Packages: EngineeringEngineering (R0)