Rotational Speed Control of Brushless Dc Motor Using Genetic Algorithm Optimized PD Controller

       Rizqi Andry Ardiansyah, Edwar Yazid

Abstract


Controlling the rotational speed of brushless DC (BLDC) motor is an essential task to improve the transient and the steady state performances under loaded condition. Rotational speed control of BLDC motor using genetic algorithm optimized proportional-derivative (PD) controller to form what the so-called the genetic algorithm-PD (GA-PD) controller is proposed in this paper. Control system is realized in a microcontroller namely a 16MHz Atmega2560 with an absolute encoder as a position sensor. The effectiveness of the GA-PD controller is tested under constant and varying step functions with the Ziegler-Nichols-PD (ZN-PD) controller as a benchmark. Experimental results show that the GA-PD controller has slower speed than the ZN-PD controller, but the latter has overshoot and small oscillations during its steady state condition as a consequent of having a fast rise time.


  http://dx.doi.org/10.14203/jet.v18.75-80

Keywords


Rotational speed; BLDC motor; PD controller; genetic algorithm

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References


K. Premkumar and B.V.Manikandan, “Adaptive neuro-fuzzy inference system based speed controller for brushless DC motor”, Neurocomputing, vol. 138, pp. 260-270, 2014. Crossref

K. Premkumar and B.V.Manikandan,”Speed control of BLDC motor using bat algorithm optimized adaptive neuro-fuzzy inference system”, Applied Soft Computing, vol. 138, pp. 260-270, 2015. Crossref

K. Premkumar and B.V.Manikandan, “Fuzzy PID supervised online ANFIS based speed controller for brushless DC motor”, Neurocomputing, vol. 157, pp. 76-90, 2015. Crossref

A.A. El-Samahy and M.A. Shamseldin, “Brushless DC motor tracking control using self-tuning fuzzy PID control and model reference adaptive control”, Ain Shams Engineering Journal, In Press, pp. 76-90, 2016. Crossref

M. Tariq, et al., “Fast response antiwindup PI speed controller of brushless DC motor drive: modelling, simulation and implementation on DSP”, Journal of Electrical Systems and Information Technology, vol. 3, pp. 1-13, 2016. Crossref

E. Gowthaman, et al., “Speed control of permanent magnet brushless DC motor using hybrid fuzzy proportional plus integral plus derivative controller”, Energy Procedia, vol. 117, pp. 1101-1108, 2017. Crossref

H.E.A. Ibrahim, F.N. Hassan, and A.O. Shomer, “Optimal PID control of a brushless DC motor using PSO and BF techniques”, Ain Shams Engineering Journal, vol. 5, pp. 391-398, 2014. Crossref

S. Zhang and Y. Wang, “The simulation of BLDC motor speed control based-optimized fuzzy PID algorithm”, in Proc. IEEE International Conference on Mechatronics and Automation, 2016, pp. 287 –292. Crossref

A. Varshney, D. Gupta, and B. Dwivedi,”Speed response of brushless DC motor using fuzzy PID controller under varying load condition”, Journal of Electrical Systems and Information Technology, vol. 4, pp. 310-321,2017. Crossref

J. Joy, and S. Ushakumari, “Performance comparison of a sensorless PMBLDC motor drive system with conventional and fuzzy logic controllers”, Procedia Technology, vol. 25, pp. 643-651, 2016. Crossref

KC AXHM5100 BLDCM user manual, Oriental Motor, 2014.

E. Yazid, M.S. Liew, S. Parman, and V.J. Kurian, “Improving the modelling capacity of Volterra model using evolutionary computing methods based on Kalman smoother adaptive filter”, Journal of Applied Soft Computing, vol. 35, pp. 695-707, 2015. Crossref


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