Speed Controller Design using Hybrid Differential Evolution Algorithm-Particle Swarm Optimization for PSMS
Downloads
The use of engines that motorized the world based on fossil fuel sources has led to many problems, such as air pollution, energy security, global warming, and climate change. To prevent further damage reducing the application of fossil fuel as a source of the motor is crucial. Hence, utilizing an electric motor could be the solution to reduce the application of motors based on fossil fuel. Among the number of electric motors, permanent magnet synchronous motor (PSMS) is becoming more popular due to their efficiency. However, the challenge here is how to design the controller of PSMS, especially the speed controller. Hence, this paper proposed a design of a speed controller of PSMS using a PI controller. The hybrid differential evolution algorithm-particle swarm optimization (DEA-PSO) is used to optimize the PI controller for better performance. From the simulation result, it is found that the proposed method can enhance the performance of PSMS.
C. Elmas and O. Ustun, "A hybrid controller for the speed control of a permanent magnet synchronous motor drive," Control Engineering Practice, vol. 16, pp. 260-270, 2008.
M. Pujiantara and M. Abdillah, "Adaptive pi controller berbasis bat algorithm (ba) dan extreme learning machine (elm) untuk kontrol kecepatan permanent magnet synchronous motor (pmsm)," JAVA Journal of Electrical and Electronics Engineering, vol. 9, 2011.
Z. Wang, C. Chung, K. Wong, and C. Tse, "Robust power system stabiliser design under multi-operating conditions using differential evolution," IET generation, transmission & distribution, vol. 2, pp. 690-700, 2008.
M. Abdillah, H. Setiadi, A. B. Reihara, K. Mahmoud, I. W. Farid, and A. Soeprijanto, "Optimal selection of LQR parameter using AIS for LFC in a multi-area power system," Journal of Mechatronics, Electrical Power, and Vehicular Technology, vol. 7, pp. 93-104, 2016.
H. Setiadi and K. O. Jones, "Power System Design using Firefly Algorithm for Dynamic Stability Enhancement," Indonesian Journal of Electrical Engineering and Computer Science, vol. 1, pp. 446-455, 2016.
H. Setiadi, N. Mithulananthan, and M. J. Hossain, "Impact of Battery Energy Storage Systems on Electromechanical Oscillations in Power Systems," in 2017 IEEE Power and Energy General Meeting, Chicago, USA, 2017.
M. Taufik, D. Lastomo, and H. Setiadi, "Small-Disturbance Angle Stability Enhancement using Intelligent Redox Flow Batteries," in 2017 4th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI 2017), Yogyakarta, Indonesia, 2017.
T. Kerdphol, K. Fuji, Y. Mitani, M. Watanabe, and Y. Qudaih, "Optimization of a battery energy storage system using particle swarm optimization for stand-alone microgrids," International Journal of Electrical Power & Energy Systems, vol. 81, pp. 32-39, 2016.
F. S. Abu-Mouti and M. E. El-Hawary, "Optimal Distributed Generation Allocation and Sizing in Distribution Systems via Artificial Bee Colony Algorithm," IEEE Transactions on Power Delivery, vol. 26, pp. 2090-2101, 2011.
D. K. Sambariya and R. Gupta, "Effective PID-PSS design using Bat algorithm for SMIB power system," in 2016 IEEE 6th International Conference on Power Systems (ICPS), 2016, pp. 1-6.
I. N. Trivedi, S. V. Purani, and P. K. Jangir, "Optimized over-current relay coordination using Flower Pollination Algorithm," in 2015 IEEE International Advance Computing Conference (IACC), 2015, pp. 72-77.
S. Ganguly and D. Samajpati, "Distributed Generation Allocation on Radial Distribution Networks Under Uncertainties of Load and Generation Using Genetic Algorithm," IEEE Transactions on Sustainable Energy, vol. 6, pp. 688-697, 2015.
K. Y. Lee and J.-B. Park, "Application of particle swarm optimization to economic dispatch problem: advantages and disadvantages," in Power Systems Conference and Exposition, 2006. PSCE'06. 2006 IEEE PES, 2006, pp. 188-192.
A. Tiguercha, A. A. Ladjici, and M. Boudour, "Optimal radial distribution network reconfiguration based on multi objective differential evolution algorithm," in 2017 IEEE Manchester PowerTech, 2017, pp. 1-6.
K. T. Chaturvedi, M. Pandit, and L. Srivastava, "Particle swarm optimization with crazy particles for nonconvex economic dispatch," Applied Soft Computing, vol. 9, pp. 962-969, 2009.
M. Nayak, K. Krishnanand, and P. Rout, "Modified differential evolution optimization algorithm for multi-constraint optimal power flow," in Energy, Automation, and Signal (ICEAS), 2011 International Conference on, 2011, pp. 1-7.
A. Karakaya and E. Karakas, "The speed control of permanent magnet synchronous motor using fuzzy logic and self tuning fuzzy PI controller," Proc. ELECO'05, 2005.
A. Karakaya and E. Karakas, "PERFORMANCE ANALYSIS OF PM SYNCHRONOUS MOTORS USING FUZZY LOGIC AND SELF TUNING FUZZY PI SPEED CONTROLS," Arabian Journal for Science & Engineering (Springer Science & Business Media BV), vol. 33, 2008.
Z. Yaou, Z. Wansheng, and K. Xiaoming, "Control of the permanent magnet synchronous motor using model reference dynamic inversion," WSEAS Transactions on Systems and Control, vol. 5, pp. 301-311, 2010.
K. Ogata and Y. Yang, "Modern control engineering," 1970.
D. Lastomo, H. Setiadi, and M. R. Djalal, "Design Controller of Pendulum System using Imperialist Competitive Algorithm," Jurnal Intek Politeknik Negeri Ujung Pandang, vol. 4, pp. 53-59, 2017.
D. Lastomo, H. Setiadi, and M. R. Djalal, "Optimization Pitch Angle Controller of Rocket System using Improved Differential Evolution Algorithm," International Journal of Advances in Intelligent Informatics, vol. 3, 2017.
M. G. Omran, A. P. Engelbrecht, and A. Salman, "Differential evolution based particle swarm optimization," in Swarm Intelligence Symposium, 2007. SIS 2007. IEEE, 2007, pp. 112-119.
S. Khamsawang, P. Wannakarn, and S. Jiriwibhakorn, "Hybrid PSO-DE for solving the economic dispatch problem with generator constraints," in Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on, 2010, pp. 135-139.
R. W. W. Atmaja, S. Herlambang, and I. Robandi, "Optimal Design of PID Controller in Interconnected Load Frequency Control using Hybrid Differential Evolution–Particle Swarm Optimization Algorithm," in Seminar on Intelligent Technology and Its Applications 2014, 2014.
D. Lastomo, H. Setiadi, and M. R. Djalal, "Optimization of SMES and TCSC using particle swarm optimization for oscillation mitigation in a multi machines power system," Journal of Mechatronics, Electrical Power, and Vehicular Technology, vol. 8, pp. 11-21, 2017.
Copyright (c) 2022 Muhammad Aldo Setiawan, Herlambang Setiadi, Rodik Wahyu Indrawan, Rizki Putra Prastio
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright
Journal of Advanced Technology and Multidiscipline (E-ISSN:2964-6162) by Universitas Airlangga, Faculty of Advanced Technology and Multidiscipline is licensed under a Creative Commons ” Attribution 4.0 International ” CC BY 4.0
Authors who publish with this journal agree to the following terms:
-
The journal allows the author to hold the copyright of the article without restrictions.
-
The journal allows the author(s) to retain publishing rights without restrictions.
-
The legal formal aspect of journal publication accessibility refers to Creative Commons Attribution (CC BY).
LICENSE TERMS
You are free to:
- Share ” copy and redistribute the material in any medium or format
- Adapt ” remix, transform, and build upon the material for any purpose, even commercially.
Under the following terms:
-
Attribution ” You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions ” You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits
