Tuning of Fractional Order Proportional Integral Derivative Controller for Speed Control of Sensorless BLDC Motor using Artificial Bee Colony Optimization Technique

  • K. Vanchinathan
  • K. R. Valluvan
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 446)


This paper introduces a novel method based on the artificial bee colony (ABC) presented for optimal tuning fractional-order proportional–integral–derivative (FOPID) controller for speed control of sensorless brushless direct current (BLDC) motor which can guarantee the desired speed control and the robustness of the closed-loop system. ABC algorithm is a recently proposed global search optimization technique which simulates the behavior of natural bees for determining the optimal parameter values. The proposed method minimizes the steady-state and transient response, i.e., steady-state error, peak overshoot time, rise time, peak time, and settling time with the help of ABC optimal tuning five-degree parameters K p , K i , K d , λ, and μ. In addition, the comparative study has been made to analyze the step response characteristics of BLDC motor drive using ABC over come conventional genetic algorithm (GA) for speed regulation of the motor. MATLAB simulation and extensive analysis of results obtained show the effectiveness of the proposed approach.


Fractional-order PID controller Sensorless BLDC motor drive Artificial bee colony optimization technique 


  1. 1.
    Ozturk SB, Toliyat HA (2011) Direct torque and indirect flux control of brushless DC motor. IEEE/ASME Trans Mechatron 16(2):351–360CrossRefGoogle Scholar
  2. 2.
    Monje CA et al (2008) Tuning and auto-tuning of fractional order controllers for industry applications. Control Eng Pract 16(7):798–812CrossRefGoogle Scholar
  3. 3.
    Ibrahim H, Hassan F, Shomer AO (2014) Optimal PID control of a brushless DC motor using PSO and BF techniques. Ain Shams Eng J 5(2):391–398CrossRefGoogle Scholar
  4. 4.
    Vanchinathan K, Valluvan KR (2015) Improvement of time response for sensorless control of BLDC motor drive using ant colony optimization technique. Int J A ppl Eng Res 10(55):6Google Scholar
  5. 5.
    Krishnan R (2001) Electric motor drives: modeling, analysis, and control. Prentice Hall, New JerseyGoogle Scholar
  6. 6.
    Vanchinathan K, Valluvan K (2016) A study of sensorless BLDC motor drives and future trends. Asian J Res Soc Sci Humanit 6(9):1863–1887Google Scholar
  7. 7.
    Gamazo-Real JC, Vázquez-Sánchez E, Gómez-Gil J (2010) Position and speed control of brushless DC motors using sensorless techniques and application trends. Sensors 10(7):6901–6947CrossRefGoogle Scholar
  8. 8.
    Pan I, Das S (2012) Intelligent fractional order systems and control: an introduction, vol 438. Springer, BerlinGoogle Scholar
  9. 9.
    Padula F, Visioli A (2011) Tuning rules for optimal PID and fractional-order PID controllers. J Process Control 21(1):69–81CrossRefzbMATHGoogle Scholar
  10. 10.
    Kesarkar AA, Selvaganesan N (2015) Tuning of optimal fractional-order PID controller using an artificial bee colony algorithm. Syst Sci Control Eng 3(1):99–105CrossRefGoogle Scholar
  11. 11.
    Rajasekhar A, Chaitanya V, Das S (2011) Fractional-order PIλDμ controller design using a modified artificial bee colony algorithm. In: Swarm, evolutionary, and memetic computing, 2011. Springer, Berlin, pp 670–678Google Scholar
  12. 12.
    Rajasekhar A, Das S, Abraham A (2013) Fractional order PID controller design for speed control of chopper fed DC motor drive using artificial bee colony algorithm. In: World Congress on nature and biologically inspired computing (NaBIC), 2013, IEEEGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Velalar College of Engineering and TechnologyErodeIndia

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