Simulasi Kendali Motor DC Penguat Terpisah Menggunakan Kendali Fuzzy-FOPID

Muhamad Asbi, Subiyanto Subiyanto, Yohanes Primadiyono


In this study, Fuzzy-Fractional Order Proportional Integral Derivative (Fuzzy-FOPID) control technique is applied to regulate the speed of a separately excited DC motor. This control technique uses a combination of two intelligent algorithm tuning methods, Fuzzy logic and Genetic Algorithm (GA). This is done to get an effective and powerful control effect. The identification of parameters in the form of Kp, Ki and Kd uses fuzzy logic and for fractional parameters in the form of μ and λ using GA. To find out the performance of this control technique several tests have been carried out using the MATLAB 2013a simulation which then the results are compared with Fractional-Order PID (FOPID) control technique where all parameters are obtained using GA tuning. In testing the speed and constant load the performance of the Fuzzy-FOPID control has a smaller overshoot value and the settling time is faster than the FOPID control. The FOPID driver has a better undershoot response of 0,25% when there is a change in the added load. But when testing the speed change, Fuzzy-FOPID control has a fast and stable response with an undershoot value of 0.875% and a 0.143% overshoot, smaller than the FOPID control. From the results of all tests, it can be concluded that Fuzzy-FOPID control is better and more efficient than FOPID control.

Dalam penelitian ini, teknik kendali Fuzzy-Fractional Order Proportional-Integral-Derivative (Fuzzy-FOPID) diterapkan untuk mengatur kecepatan motor DC penguat terpisah. Teknik kendali ini menggunakan gabungan dua metode penalaan algoritma cerdas yaitu logika fuzzy dan Algoritma Genetika (GA). Hal ini dilakukan untuk mendapatkan efek kendali yang efektif dan kuat. Penalaan  parameter Kp, Ki, dan Kd menggunakan logika fuzzy dan untuk parameter fractional μ dan λ menggunakan GA. Untuk mengetahui kinerja dari teknik kendali ini telah dilakukan beberapa tes menggunakan simulasi MATLAB 2013a yang kemudian hasilnya dibandingkan dengan teknik kendali lain yaitu teknik kendali FOPID dimana semua parameternya didapat dengan menggunakan penalaan GA. Pada pengujian kecepatan dan beban konstan performa kendali Fuzzy-FOPID memiliki nilai overshoot yang lebih kecil dan settling time lebih cepat dibanding kendali FOPID. Pengendali FOPID memiliki respon undershoot yang lebih baik sebesar 0,25 % ketika tejadi  penambahan  beban. Namun ketika dilakukan pengujian perubahan kecepatan, kendali Fuzzy-FOPID memiliki respon yang cepat stabil dengan nilai undershoot 0,875 % dan overshoot 0,143%, lebih kecil dibandingkan dengan kendali FOPID. Dari hasil seluruh pengujian dapat disimpulkan bahwa kendali Fuzzy-FOPID lebih baik dan effisien dibandingkan dengan kendali FOPID.


Fuzzy Fractional Order Proportional-Integral-Derivative, separately excited DC motor, fuzzy logic, Genetic Algorithm, simulation

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S. K. Gupta, P. Varshney, “Fractional fuzzy PID controller for speed control of DC motor,” in Proceeding of the Third International Conference on Advances in Computing and Communication, 2013, pp. 1–4.

S. A. Deraz, “Genetic tuned PID controller based speed control of DC motor drive,” International Journal of Engineering Trends and Technology, vol.17 no.2, pp. 88–93, Nov. 2014.

R. Zhang, L. Song, J. Yang, T. Hoffman, "DC Motor Speed Control System Simulation Based on Fuzzy Self-tuning PID", in Fuzzy Information and Engineering vol. 2, Advances in Intelligent and Soft Computing, vol. 62, B.Y. Cao, T.F. Li, C.Y. Zhang, Ed. Springer, Berlin, Heidelberg, 2009, pp. 967-975.

N. Kumar, H. Gupta, R. Choudhary, “Analysis fuzzy self tuning of PID controller for DC motor drive,” International Journal of IT and Knowledge Management, Special Issue (ICFTEM-2014), pp. 148–152, May 2014.

A. Rajasekhar, R. Kumar Jatoth, A. Abraham, “Design of intelligent PID/PIλDμ speed controller for chopper fed DC motor drive using opposition based artificial bee colony algorithm,” Engineering Applications of Artificial Intelligence, vol. 29, pp.13–32, March 2014.

U. Kumar Bansal, R. Narvey, “Speed control of DC motor using fuzzy PID controller,” Advance in Electronic and Electric Engineering, vol.3 no.9, pp. 1209–1220, 2013.

V. K. A. S. Jhunghare, "Fractional order PID controller for speed control of DC motor using genetic algorithm,” International Journal for Scientific Research and Development, vol.2 no.2, pp. 896–898, 2014.

A. S. Chopade, S. W. Khubalkar, A. S. Junghare, M. V. Aware, “Fractional order speed controller for buck-converter fed DC motor,” in Proceedings of the 2016 IEEE 1st International Conference on Control, Measurement and Instrumentation (CMI), 2016, pp. 331–335.

S. Das, I. Pan, S. Das, “Fractional order fuzzy control of nuclear reactor power with thermal-hydraulic effects in the presence of random network induced delay and sensor noise having long range dependence,” Energy Conversion and Management, vol. 68, pp. 200–218, April 2013.

R. S. Barbosa, I. S. Jesus, M. F. Silva, “Fuzzy reasoning in fractional-order PD controllers,” in New Aspects of Applied Informatics, Biomedical Electronics & Informatics and Communications, 2010, pp. 252–257.

L. Liu, F. Pan, D. Xue, “Variable-order fuzzy fractional PID controller,” ISA Transactions, vol. 55, pp. 227–233, March 2015.

R. Sharma, K. P. S. Rana, V. Kuma, “Performance analysis of fractional order fuzzy PID controllers applied to a robotic manipulator,” Expert Systems with Applications, vol. 41 no.9, pp. 4274–4289, July 2014.

N. J. Patil, D. R. H. Chile, D. L. M. Waghmare, “Fuzzy adaptive controllers for speed control of PMSM drive,” International Journal of Computer Applications, vol. 1 no.11, pp. 91–98, Febr. 2010.

B. M. Vinagre, I. Podlubny, L. Dorcak, V. Feliu, “On fractional PID controllers: a frequency domain approach,” in IFAC Proceedings Volumes (IFAC-Papers Online), 2000, vol. 33 no. 4, pp. 51–56.

P. Varshney, S. K. Gupta, “Implementation of fractional fuzzy PID controllers for control of fractional-order systems,” in Proceedings of The 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2014, pp. 1322–1328.

J. Cao, J. I. N. Liang, B. Cao, “Optimization of fractional order PID controllers based on genetic algorithms,” in Proceedings of The Fourth International Conference on Machine Learning and Cybernetics, Aug. 2005, pp. 5686–5689.

M. P. Lazarević, S. A. Batalov, T. S. Latinović, “Fractional PID controller tuned by genetic algorithms for a three DOF’s robot system driven by DC motors,” in IFAC Proceedings Volumes (IFAC-PapersOnline), vol. 46 no. 1, 2013, pp. 385–390.

E. E. Vladu, T. L. Dragomir, “Controller Tuning Using Genetic Algorithms,” in Proceedings of The first Romanian-Hungarian Joint Symposium on Applied Computational Intelligence, 2004, pp. 1–10.

A. Y. Jaen-Cuellar, R. D. J. Romero-Troncoso, L. Morales-Velazquez, R. A. Osornio-Rios, “PID-controller tuning optimization with genetic algorithms in servo systems,” International Journal of Advanced Robotic Systems, vol.10 no.9, pp. 324, 2013.

S. Kumar Suman, V. Kumar Giri, “Genetic algorithms techniques based optimal PID tuning for speed control of DC motor,” American Journal of Engineering and Technology Management, vol.1 no.4, pp. 59–64, Nov. 2016.

“Demos: Chopper-fed DC motor drive.” [Online]. Available:

M. M. F. Algreer, Y. R. M. Kuraz, “Design fuzzy self tuning of PID controller for chopper-fed DC motor drive,” Al-Rafidain Engineering, vol. 16 no.2, pp. 54–66, 2008.

M. Moafi, M. Marzband, M. Savaghebi, J. M. Guerrero, “Energy management system based on fuzzy fractional order PID controller for transient stability improvement in microgrids with energy storage,” International Transactions on Electrical Energy Systems, vol. 26 no.10, pp. 2087–2106, 2016.


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