Investigation of Different Rules Size FLSC Performance Applied to Induction Motor Drive

Authors

  • M. H. N. Talib Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka
  • Z. Ibrahim Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka
  • Z. Rasin Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka
  • J. Mat Lazi Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka
  • M. Azri Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka

Keywords:

Induction Motor, FLC, Speed Drive, Fuzzy Rules,

Abstract

Fuzzy Logic Controller (FLC) has been widely used in speed controller due to its superior performance results. It is suitable when the system is difficult to model mathematically due to its nonlinearity and complexity. There are three common number of rules design which are commonly used in FLSC known as 49, 25 and 9 rules. However, the majority of the previous research report mainly focused on the dedicated rules size design either 49, 25 or 9 rules for the optimum performance. There is lack of performance comparison between 49, 25 and 9 rules size. Thus, it is difficult to understand how the rules size affects the motor performance. This research tries to fill up the gap by comparing the controller performance using the same platform. The fuzzy logic speed controllers (FLSC) with a different type of rules base are applied to the induction motor drive system. The FLSC with 49, 25 and 9 rules are investigated through MATLAB/SIMULINK and performance comparisons are made covering a wide speed range operations and load disturbance. The simulation results are evaluated based on the rise time (Tr), overshoot (OS), settling time (Ts), Integral Absolute Error (IAE) and Integral Time Absolute Error (ITAE) for transient and steady state condition. It is shown that the smaller size of rules does not necessarily degrade the performance.

References

Z. Ibrahim and E. Levi, "A Comparative Analysis of Fuzzy Logic and PI Speed Control in High Performance AC Drives using Experimental Approach," IEEE Transactions on Industry Applications, Vol. 38, No. 38, pp. 1210-1218, Sep./Oct. 2002.

M. N. Uddin, T. S. Radwan, and M. Azizur Rahman, "Performances of Fuzzy Logic Based Indirect Vector Control for Induction Motor Drive," IEEE Transactions on Industry Applications, Vol. 38, No. 38, pp. 1219-1225, Sep./Oct. 2002.

S. Hameed, B. Das, and V. Pant, "Reduced Rule Base Self Tuning Fuzzy PI Controller for TCSC," International Journal of Electrical Power & Energy Systems, Vol. 32, No. 32, pp. 1005-1013, Nov. 2010.

B. Bhushan, M. Singh, and P. Prakash, "Performance Analysis of Field Oriented Induction Motor using Fuzzy PI and Fuzzy Logic based Model Reference Adaptive Control," International Journal of Computer Applications, Vol. 17, No. 17, pp. 5-12, 2011.

A. Saghafinia, P. Hew Wooi, M. N. Uddin, and K. S. Gaeid, "Adaptive Fuzzy Sliding-Mode Control Into Chattering-Free IM Drive," IEEE Transactions on Industry Applications, Vol. 51, No. 51, pp. 692-701, 2015.

F. Gang, "A Survey on Analysis and Design of Model-Based Fuzzy Control Systems," IEEE Transactions on Fuzzy Systems, Vol. 14, No. 14, pp. 676-697, 2006.

R. Singh, A. K. Singh, and P. Kumar, "Self-tuned approximated simplest fuzzy logic controller based shunt active power filter," in International Conference on nergy Economics and Environment (ICEEE), 2015, pp. 1-6.

L. Yang, Y. Li, Y. Chen, and Z. Li, "A Novel Fuzzy Logic Controller for Indirect Vector Control Induction Motor Drive," in 7th World Congress on Intelligent Control and Automation, 2008, pp. 24-28.

İ. Eminoğlu and İ. H. Altaş, "The Effects of the Number of Rules on the Output of a Fuzzy Logic Controller Employed to a PMDC Motor," Computers & Electrical Engineering, Vol. 24, No. 24, pp. 245-261, 1998.

F. Betin, D. Pinchon, and G. A. Capolino, "Fuzzy Logic Applied to Speed Control of a Stepping Motor Drive," IEEE Transactions on Industrial Electronics, Vol. 47, No. 47, pp. 610-622, Jun. 2000.

C. Y. Kumar B, Shrivastava V., "Efficacy of Different Rule Based Fuzzy Logic Controllers for Induction Motor Drive " International Journal of Machine Learning and Computing, Vol. 2, No. 2, pp. 131-137, 2012.

M. H. N. Talib, Z. Ibrahim, N. A. Rahim, and A. S. A. Hasim, "Comparison Analysis of Indirect FOC Induction Motor Drive using PI, Anti-Windup and Pre Filter Schemes," International Journal of Power Electronics and Drive Systems (IJPEDS), Vol. 4, No. 4, pp. 219-229, 2014.

Z. Jin and B. K. Bose, "Evaluation of Membership Functions for Fuzzy Logic Controlled Induction Motor Drive," in 28th Annual Conference of the Industrial Electronics Society, 2002, pp. 229-234.

M. H. N. Talib, Z. Ibrahim, N. A. Rahim, and A. S. A. Hasim, "Performance Improvement of Induction Motor Drive Using Simplified FLC Method," in 16th International Power Electronics and Motion Control Conference and Exposition, Antalya, Turkey, 2014, pp. 843-848.

W. Shun-Chung and L. Yi-Hua, "A Modified PI-Like Fuzzy Logic Controller for Switched Reluctance Motor Drives," IEEE Transactions on Industrial Electronics, Vol. 58, No. 58, pp. 1812-1825, 2011.

L. Han-Xiong and H. B. Gatland, "Conventional fuzzy control and its enhancement," IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, Vol. 26, No. 26, pp. 791-797, Oct. 1996.

Downloads

Published

2017-09-01

How to Cite

Talib, M. H. N., Ibrahim, Z., Rasin, Z., Mat Lazi, J., & Azri, M. (2017). Investigation of Different Rules Size FLSC Performance Applied to Induction Motor Drive. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(2-8), 165–169. Retrieved from https://jtec.utem.edu.my/jtec/article/view/2649