i-manager Publications

A Neuro-Fuzzy Controller for Doubly FED Asynchronous Motor Drive

Azeddine Chaiba*, Rachid Abdessemed**, M. Lokmen Bendass***

* Department of Electrical Engineering, Faculty of Technology, University of Setif, Algeria.

**,*** LEB Research Laboratory, University of Batna, Algeria.

Periodicity:July - September'2010
DOI : https://doi.org/10.26634/jee.4.1.1246

Abstract

In this paper neuro-fuzzy controller for Doubly Fed Asynchronous Motor (DFAM) drive is proposed. First, a mathematical model of DFAM written in an appropriate d-q reference frame is established to investigate simulations. In order to control the rotor currents of DFAM, a torque tracking control law is synthesized using PI controllers, under conditions of the stator side power factor is controlled at unity level. A four layer Neural Network (NN) is used to adjust input and output parameters of membership functions in a fuzzy logic controller (FLC). The back propagation learning algorithm is used for training this network. The performances of neuro-fuzzy controller (NFC) which is based on the torque tracking control algorithm are investigated and compared to those obtained from the PI controller. Results obtained in Matlab/Simulink environment show that the NFC is more robust, superior dynamic performance and hence found to be a suitable replacement of the conventional PI controller for the high performance drive applications.

Keywords

Doubly-Fed Asynchronous Motor (DFAM), Torque Tracking Control, Neuro-Fuzzy controller

How to Cite this Article?

Azeddine Chaiba, Rachid Abdessemed and M. Lokmen Bendaas (2010). A Neuro-Fuzzy Controller For Doubly Fed Asynchronous Motor Drive. i-manager’s Journal on Electrical Engineering, 4(1), 8-15. https://doi.org/10.26634/jee.4.1.1246

References

[1]. Muller, S., Deicke, M., & Doncker, R.W. De. (2000). “Adjustable speed generators for wind turbines based on doubly-fed induction machines and 4-quadrant IGBT converters linked to the rotor”. IEEE IAS. Rome.

[2]. Bose, B.K. (1996). “Power Electronics and Variable Frequency Drives Technology and Applications”. NewYork, Press.

[3]. Won, C.Y. & Bose, B.K. (1992). “An Induction Motor Servo System with Improved Sliding Mode Control”. IEEE Conf. Rec. Of IECON'92, 60-66.

[4]. Leonhard, W. (1997). Control Electrical Drives, Springier verlag Berlin Heidelberg, Printed in Germany

[5]. Wang, S., and Ding, Y. (1993). “Stability Analysis of Field Oriented Doubly Fed induction Machine Drive Based on Computed Simulation”. Electrical Machines and Power Systems (Taylor & Francis).

[6]. Debiprasad, Panda, Eric, L., Benedict, Giri Venkataramanan & Thomas A. Lipo. (2001). “A Novel Control Strategy for the Rotor Side Control of a Doubly-Fed Induction Machine”. IEEE. 1695-1702.

[7]. Bayindir, M.I., Can, H., Akpolat, Z.H., Özdemir, M., & Akin, E. (2005). “Application of reaching law approach to the position control of a vector controlled induction motor drive”. Electrical Engineering, 87. 207-215.

[8]. Qingding, G., Limei. W & Ruifu, L. (1997). “Robust fuzzy variable structure control of PMLSM servo system”, IEEE International conference on intelligent processing systems, Beijing, China. 675-679.

[9]. Elmas, C., Ustun, O., & Sayan, H.H, (2008). “A neurofuzzy controller for speed control of a permanent magnet synchronous motor drive”. Expert Systems with Applications, 34.1, 657-664.

[10]. Gökbulut, M., Dandil, B., & Bal, C., (2006). A hybrid neuro-fuzzy controller for brushless DC motors. Lecture Notes in Computer Science, 3949. 125-132.

[11]. Gökbulut, M., Dandil. B., & Bal. C, (2007). Development and controller for brushless DC drives. Intelligent Automation and Soft Computing, 13. 415-427.

[12]. Jang, J.S.R., & Sun, C.T. (1995). “Neuro-fuzzy modelling and control”. Proceeding of the IEEE. 83. 378- 405.

[13]. Tapia, A., Tapia, GOstolaza, J.X., & Saenz, J. R. (2003). Modiling and control of a wind turbine driven doubly fed induction generator. IEEE transactions on energy conversion.18. 194-204.

[14]. Zhang, L. & Watthanasarn, C. (1998). “A matrix converter excited Doubly-fed Induction Machine as a wind power generator”, IEE conference Publication N456, Power Electronics and variable speed drives, 532-537.

[15]. Gaillard, A., Karimi, S., Poure, P., & Saadate. (2007). “Fault tolerant back-to-back converter topology for wind turbine with doubly fed induction generator ”, International Review of Electrical Engineering. 629-636.

[16]. Pena, R., Clare, J.C., & Asher, G.M. (1996). “Doubly fed induction generator using back-to-back PWM converters and its application to variable-speed windenergy generation. IEE Proc Part B. 143. 231-241.

[17]. Vieira, J., Dias, F.M., & Mota, A., (2004). “Artificial neural networks and neuro-fuzzy systems for modelling and controlling real systems: A comparative study”. Engineering Applications of Artificial Intelligence. 17.265- 273.

	North Americas,UK, Middle East,Europe		India	Rest of world
	USD	EUR	INR	USD-ROW
Pdf	35	35	200	20
Online	35	35	200	15
Pdf & Online	35	35	400	25

A Neuro-Fuzzy Controller for Doubly FED Asynchronous Motor Drive

Abstract

Keywords

How to Cite this Article?

References

If you have access to this article please login to view the article or kindly login to purchase the article

Purchase Instant Access

Options for accessing this content: