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Analysis and Implementation of ANFIS-based Rotor Position Controller for BLDC Motors
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  • Journal title : Journal of Power Electronics
  • Volume 16, Issue 2,  2016, pp.564-571
  • Publisher : The Korean Institute of Power Electronics
  • DOI : 10.6113/JPE.2016.16.2.564
 Title & Authors
Analysis and Implementation of ANFIS-based Rotor Position Controller for BLDC Motors
Navaneethakkannan, C.; Sudha, M.;
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This study proposes an adaptive neuro-fuzzy inference system (ANFIS)-based rotor position controller for brushless direct current (BLDC) motors to improve the control performance of the drive under transient and steady-state conditions. The dynamic response of a BLDC motor to the proposed ANFIS controller is considered as standard reference input. The effectiveness of the proposed controller is compared with that of the proportional integral derivative (PID) controller and fuzzy PID controller. The proposed controller solves the problem of nonlinearities and uncertainties caused by the reference input changes of BLDC motors and guarantees a fast and accurate dynamic response with an outstanding steady-state performance. Furthermore, the ANFIS controller provides low torque ripples and high starting torque. The detailed study includes a MATLAB-based simulation and an experimental prototype to illustrate the feasibility of the proposed topology.
ANFIS controller;BLDC motor;Fuzzy PID controller;MATLAB/Simulink;PID controller;
 Cited by
J. Y. Hung, W. Gao, and J. C. Hung, “Variable structure control: a survey,” IEEE Trans. Ind. Electron., Vol. 40, No. 1, pp. 2-22, Feb. 1993. crossref(new window)

E. Cerruto, A. Consoli, A. Raciti, and A. Testa, “ A robust adaptive controller for PM motor drives in robotic application,” IEEE Trans. Power Electron., Vol. 10, No. 1, pp. 62-71, Jan. 1995. crossref(new window)

N. Hemati, J. S. Thorp, and M. C. Leu, “Robust nonlinear control of brushless dc motors for direct drive robotic applications,” IEEE Trans. Ind. Electron., Vol. 37, No. 6, pp. 460-468, Dec. 1990. crossref(new window)

U. Neethu and V. R. Jisha, "Speed control of brushless DC motor: a comparative study," in IEEE International Conference on Power Electronics, Drives and Energy Systems(PEDES), pp. 1-5, Dec. 2012.

A. Sathyan, N. Milivojevic, Y.-J. Lee, and M. Krishnamurthy, “An FPGA based novel digital PWM control scheme for BLDC motor drives,” IEEE Trans. Ind. Electron., Vol. 56, No. 8, pp. 3040-3049, Aug. 2009. crossref(new window)

Metin Demirtas, “Off-line tuning of a PI speed controller for a permanent magnet brushless DC motor using DSP,” Energy Conversion and Management, Vol. 52, No. 1, pp. 264-273, Jan. 2011. crossref(new window)

A. S. O. Al-Mashakbeh, “Proportional integral and derivative control of brushless DC motor,” European Journal of Scientific Research, Vol. 35, No. 2, pp. 198-203, Aug. 2009.

J. C. Basilio and S. R. Matos, “Design of PI and PID controllers with transient performance specification,” IEEE Trans. Edu., Vol. 45, No. 4, pp. 364-370, Nov. 2002. crossref(new window)

R. Arulmozhiyal and K. Baskaran, “Implementation of fuzzy PI controller for speed control of IM using FPGA,” Journal of Power Electronics, Vol. 10, No. 1, pp. 65-71, 2010. crossref(new window)

S. V. Wadnerkar, M. M. Bhaskar, T. R. Das, and A. D. RajKumar, “A new fuzzy logic based modeling and simulation of a switched reluctance motor,” Journal of Electrical Engineering & Technology, Vol. 5, No. 2, pp. 276-281, Jun. 2010. crossref(new window)

N. S. Kumar and C. S. Kumar, “Design and implementation of adaptive fuzzy controller for speed control of brushless DC motors,” International Journal of Computer Applications, Vol. 1, No. 27, pp. 46-51, Feb. 2010. crossref(new window)

M. Cunkas and O. Aydoğdu, “Realization of fuzzy logic controlled brushless DC motor drives using Matlab/Simulink,” Mathematical and Computational Applications, Vol. 15, No. 2, pp. 218-229, Aug. 2010. crossref(new window)

J. Sun, Y. Chai, C. Su, Z. Zhu, and X. Luo, "BLDC motor speed control system fault diagnosis based on LRGF neural network and adaptive lifting scheme," Applied Soft Computing, Vol. 14, Part C, pp. 609-622, Jan. 2014. crossref(new window)

Z. Cheng, C. Hou, and X. Wu, "Global sliding mode control forb DC motors by neural networks," in Proceedings of AICI, No. 4, pp. 3-6, 2009.

M. Gokbulut, B. Dandil, and C. Bal, A hybrid neuro-fuzzy controller for brushless DC motors, Artificial Intelligence and Neural Networks, Springer, Vol. 3949, pp. 125-132, 2006.

A. Rubaai, M. J. Castro-Sitiriche, and A. R. Ofoli, “Design and implementation of parallel fuzzy PID controller for high-performance brushless motor drives: an integrated environment for rapid control prototyping,” IEEE Trans. Ind. Appl., Vol. 44, No. 4, pp. 1090-1098, Jul./Aug. 2008. crossref(new window)

M. J. Er and Y. Gao, “Robust adaptive control of robot manipulators using generalized fuzzy neural networks,” IEEE Trans. Ind. Electron., Vol. 50, No. 3, pp. 620-628, Jun. 2003. crossref(new window)

C.-H. Lee and C.-C. Teng, “Identification and control of dynamic systems using recurrent fuzzy neural Networks,” IEEE Trans. Fuzzy Syst., Vol. 8, No. 4, pp. 349-366, Aug. 2000. crossref(new window)

Q. C. Zhang and M. Jiang, “Adaptive neuro-fuzzy control of BLDCM based on back-EMF,” Journal of Computer Information Systems, Vol. 7, No. 12, pp. 4560-4567, Oct. 2011.

V. M. Varatharaju, B. Mathur, and Udhayakumar, “Adaptive controllers for permanent magnet brushless DC motor drive system using adaptive network based fuzzy interference system,” American Journal of Applied Sciences, Vol. 8, No. 8, pp. 810-815, Aug. 2011. crossref(new window)

K. Premkumar and B. V. Manikandan, “Adaptive neurofuzzy inference system based speed controller for brushless DC motor,” Neurocomputing, Vol. 138, No.1, pp. 260-270, Aug. 2014. crossref(new window)

A. H. Niasar, A. Vahedi, and H. Moghbelli, "Speed control of a brushless DC motor drive via adaptive neuro fuzzy controller based on emotional learning algorithm," in Proceedings of the 8th International Conference on Electrical Machines and Systems(ICEMS), Vol. 1, pp. 230-234, Sep. 2005.