Email this article 
Hide
Show all
Kendali Kecepatan Motor Induksi 3 Fase Berbasis Particle Swarm Optimization (PSO)
Abstract
ABSTRAK
Motor induksi secara struktur dan kendali standarnya dirancang untuk bekerja pada kecepatan nominal, sehingga sulit mengendalikan kecepatan sesuai kebutuhan karena akan mengubah konstruksi motor. Penelitian tentang pengendalian motor induksi agar semudah mengendalikan motor DC sudah banyak dilakukan oleh peneliti, salah satunya adalah dengan kendali skalar. Kendali skalar banyak digunakan karena memiliki keunggulan sederhana, biaya murah, mudah didesain dan diimplementasikan, serta yang paling penting tidak memerlukan parameter dari motor induksi. Penggunaan kendali skalar yang telah dilengkapi pengendali PID penalaan otomatis, dengan parameter yang telah dioptimalkan algoritma Particle Swarm Optimization (PSO), akan memudahkan pengendalian kecepatan motor induksi tiga fase pada kecepatan beragam. Simulasi penalaan otomatis PID menggunakan PSO telah dilakukan dengan LabView, dengan karakteristik maksimal 10% overshoot, 1% error steady state dan rise time kurang dari 2 milidetik. Sementara dalam pengujian real time dengan MyRIO hasilnya tanpa overshoot, 5.5% error steady state maksimal dan rise time maksimal 5 detik.
Kata kunci:Â Kendali skalar, PID, Particle Swarm Optimization, LabView
Â
ABSTRACT
Induction motor is designed at nominal speed as default, we have to change its stucture to obtain dessired speed. Many researchers developt method how to control induction motor as simple as DC motor, one of the methods is scalar control. Scalar control has several benefits, such as simply, low cost, easily designed and implemented, and the main banefit is no necessary motor parameters. Using scalar control with PID controller that optimized Partical Swarm Optimization (PSO) algoritm, will ease to control 3 phase induction motor variant speed. Simulation auto tunning using PSO has done on LabView, it has some characteristic, they are 10% overshoot, 1% steady state error, and rise time within 2ms. In other hand, real time test using MyRIO got no overshoot, 5.5% steady state error maximal, and rise time maximal 5 s characteristic.
Keywords:Â Scalar control, PID, Particle Swarm Optimization, LabView
Keywords
Full Text:
PDF (Bahasa Indonesia)References
Ali, J. A., Hannan, M. A., & Mohamed, A. (2014). PSO algorithm for three phase induction motor drive with SVPWM switching and V/f control. Conference Proceeding - 2014 IEEE International Conference on Power and Energy, (pp. 250–254).
Alsofyani, I. M., & Idris, N. R. N. (2013). A review on sensorless techniques for sustainable reliablity and efficient variable frequency drives of induction motors. Renewable and Sustainable Energy Reviews, 24, 111–121.
Bhavin, A, Khichada, Chusdashma, K. J., M, Vyas. Darshan., & D, Shiyal. Jignesh. (2016). 3-Phase Induction Motor Parameter Monitoring and Analysis Using Labview. International Journal of Electrical Engineering & Technology (IJEET), 7(6), 81–91.
Chao, K. H., Lin, Y. S., & Lai, U. D. (2015). Improved particle swarm optimization for maximum power point tracking in photovoltaic module arrays. Applied Energy, 158, 609–618.
Ferdiansyah, I., Sutedjo, Yanaratri, D. S., & Raharja, L. P. S. (2019). Comparative study of maximum boost control Z-source inverter with SPWM-VSI for induction motor drive. International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2018, (pp. 380–384).
Hannan, M. A., Ali, J. A., Mohamed, A., & Hussain, A. (2018). Optimization techniques to enhance the performance of induction motor drives: A review. Renewable and Sustainable Energy Reviews, 81, 1611–1626.
International Energy Agency. (2017). Global EV Outlook 2017. In IEA Pub.
Nhizanth, A. G. R., & Gopalakrishnan, S. K. (2015). Stepper Motor Control using LabVIEW and NI-myRIO Saranathan College of Engineering Trichy , India. 2(12), 478–480.
Ramli, L., Sam, Y. M., Mohamed, Z., Khairi Aripin, M., Fahezal Ismail, M., & Ramli, L. (2015). Composite nonlinear feedback control with multi-objective particle swarm optimization for active front steering system. Jurnal Teknologi, 72(2), 13–20.
Reza, C. M. F. S., Islam, M. D., & Mekhilef, S. (2014). A review of reliable and energy efficient direct torque controlled induction motor drives. Renewable and Sustainable Energy, 37, 919-932.
Rind, S. J., Ren, Y., Hu, Y., Wang, J., & Jiang, L. (2017). Configurations and Control of Traction Motors for Electric Vehicles : A Review. 3(3), 13–14.
Saidur, R., Mekhilef, S., Ali, M. B., Safari, A., & Mohammed, H. A. (2012). Applications of variable speed drive (VSD) in electrical motors energy savings. Renewable and Sustainable Energy Reviews, 16(1), 543–550.
Salem, F., Awadallah, M. A., & Bayoumi, E. H. E. (2015). Model Predictive Control for Deadbeat Performance of Induction Motor Drives. 14, 303–311.
Suetake, M., Da Silva, I. N., & Goedtel, A. (2011). Embedded DSP-based compact fuzzy system and its application for induction-motor V/f speed control. IEEE Transactions on Industrial Electronics, 58(3), 750–760.
DOI: https://doi.org/10.26760/elkomika.v8i3.477
Refbacks
_______________________________________________________________________________________________________________________
ISSN (print) : 2338-8323 | ISSN (electronic) : 2459-9638
Publisher:
Department of Electrical Engineering Institut Teknologi Nasional Bandung, Indonesia
Address: 20th Building Institut Teknologi Nasional Bandung PHH. Mustofa Street No. 23 Bandung 40124, Indonesia
Contact: +627272215 (ext. 206)
Email: jte.itenas@itenas.ac.id
________________________________________________________________________________________________________________________
Jurnal ini terlisensi oleh Creative Commons Attribution-ShareAlike 4.0 International License.
