Direct Field-Oriented Control using Fuzzy Logic Type-2 for Induction Motor with Broken Rotor Bars

Direct Field-Oriented Control using Fuzzy Logic Type-2 for Induction Motor with Broken Rotor Bars

Belhamdi Saad* Amar.Goléa

Electrical Engineering Lab., LGE, University of M’sila, M’Sila, Algeria

LGEB Laboratories, Biskra University, Algeria

Corresponding Author Email: 
bsaad1@yahoo.fr
Page: 
203-212
|
DOI: 
https://doi.org/10.18280/ama_c.720401
Received: 
13 February 2017
|
Accepted: 
25 February 2017
|
Published: 
31 December 2017
| Citation

OPEN ACCESS

Abstract: 

In the paper an analysis of the Direct Field Control Fuzzy logic type-2 of induction motor drive with broken rotor bars is presented. The simplicity of traditional regulators makes them popular and the most used solution in the nowadays industry. However, they suffer from some limitations and cannot deal with nonlinear dynamics and system parameters variation. In the literature, several strategies of adaptation are developed to alleviate these limitations. Artificial intelligent has found high application in most nonlinear systems same as motors drive. Because it has intelligence like human but there are no sentimental against human like angriness and.... Artificial intelligent is used for various points like approximation, control, and monitoring. Because artificial intelligent techniques can use as controller for any system without requirement to system mathematical model, it has been used in electrical drive control. With this manner, efficiency and reliability of drives increase and volume, weight and cost of them decrease.

Keywords: 

Induction motor, Modeling, Direct Vector Control, Fuzzy logic type-2, Broken bar.

1. Introduction
2. Modeling the Induction Motor for Its Control
3. Order by Fuzzy Logic-Type-2
4. Results and Analysis
5. Conclusion
Appendix
  References

1. Q. Liang, J. M. Mendel, Interval type-2 fuzzy logic systems: Theory and design, IEEE Trans. Fuzzy Syst, vol. 8, no. 5, pp. 535–550, 2000.

2. J.M. Mendel, R.I. John, F. Liu, Interval type-2 fuzzy logic systems made simple, IEEE Transactions on Fuzzy Systems, vol. 14, no. 6, pp. 808–821, 2006.

3. J. M. Mendel, R. I. B. John. Type-2 fuzzy sets made simple, IEEE Transactions on Fuzz Systems, vol. 10, No. 2, pp. 117–127, 2002. 

4. I. Takahashi, T. Noguchi, A New Quick Response and High-Efficiency Control Strategy of an Induction Motor, IEEE Trans. On IA, vol. 22, no. 5, pp. 820-827, 1986.

5. H. Hagras. Type-2 FLCs, A new generation of fuzzy controllers, IEEE Computational Intelligence Magazine, vol. 2, pp. 30-43, 2007.

6. Vinod Kumar, R. R. Joshi, Hybrid Controller based Intelligent Speed Control of Induction Motor, Journal of Theoretical and Applied Information Technology, vol. 3, no. 1, pp. 71- 75, 2006. 

7.   Belhamdi, S, Goléa, A Direct Torque Control for Induction Motor with broken bars Using Fuzzy Logic Type-2 AMSE Journals, Advances C, vol. 70, no.1-2, pp.15-28, 2015. 

8. Belhamdi, S, Goléa, A, Fuzzy logic Control of Asynchronous Machine Presenting Defective Rotor Bars, AMSE Journals, Advances C, vol. 68, no. 2, pp. 54-63, 2013.

9. O. Castillo, P. Melin, A review on the design and optimization of interval type-2 fuzzy controllers, Applied Soft Computing, vol. 12, pp. 1267–1278, 2012.

10. J.M. Mendel, R.I. John, F. Liu, Interval type-2fuzzy logic systems made simple, IEEE Transactions on Fuzzy Systems, vol. 14, no. 6, pp. 808–821, 2006.

11. Ashok Kusagur, F. Kodad, B.V. Sankar Ram, Al based design of a fuzzy logic scheme for speed control of induction motors using SVPWM technique, Proc, Int. Jr. Comp. Sci & Network Security, vol. 9, no. 1, pp. 74-80, 2009.