Meta-heuristic algorithm-based optimal PID controller design for Power Converters
Year 2021,
Volume: 1 Issue: 2, 67 - 72, 05.09.2021
Cihan Demircan
,
Onur Vahip Güler
Ali Keçebaş
Abstract
The DC-DC converters are one of the important components of the renewable energy systems. In this study, meta-heuristic-based intelligent control schemes are applied, such as, proportional-integrator (PI), proportional-derivative (PD) and proportional-integrator-derivative (PID) control. The gain parameters of the PID controlled DC-DC buck or step-down converter is optimized with the artificial bee colony (ABC) algorithm. The obtained results indicate that PID control is better than the others.
References
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- [25] Demircan C., Bayrakçı H.C., Keçebaş A. “Machine Learning-based improvement of empiric models for an accurate estimating process of global solar radiation”, Sustainable Energy Technologies and Assessments, 37(2020) 100574, doi: 10.1016/j.seta.2019.100574.
- [26] Özkaraca O., Keçebaş A., Demircan C. “Comparative thermodynamic evaluation of a geothermal power plant by using the advanced exergy and artificial bee colony methods”, Energy, 156(2018) 169-180, doi: 10.1016/j.energy.2018.05.095
Year 2021,
Volume: 1 Issue: 2, 67 - 72, 05.09.2021
Cihan Demircan
,
Onur Vahip Güler
Ali Keçebaş
References
- [1] Xiao S., Wang H., Wang W., Huang Z., Zhou X., Xu M. “Artificial bee colony algorithm based on adaptive neighborhood search and Gaussian perturbation”, Applied Soft Computing Journal 100 (2021) 106955, doi: 10.1016/j.asoc.2020.106955.
- [2] Ma L., Zhang Y., Yang X., Ding S., Dong L. “Quasi-Continuous Second-Order Sliding Mode Control of Buck Converter”, IEEE Access 6(2018) 17859-17867, doi: 10.1109/ACCESS.2018.2795027.
- [3] Yang J, Wu B., Li S., Yu X. “Design and qualitative robustness analysis of an DOBC approach for DC-DC buck converters with unmatched circuit parameter perturbations”, IEEE Trans. Circuits Syst. I, Reg. Papers 63(4) (2016), 551-560, doi: 10.1109/TCSI.2016.2529238.
- [4] Ding S., Zheng W., Sun J., Wang J. “Second-order sliding mode controller design and its implementation for buck converters”, IEEE Trans. Ind. Informatics 14,(5) (2018),1990-2000, doi: 10.1109/TII.2017.2758263.
- [5] Yuan Y., Chang C., Zhou Z., Huang X., Xu Y. “Design of a Single-Input Fuzzy PID controller based on genetic optimization scheme for DC-DC buck converter”, International Symposium on Next-Generation Electronics (ISNE), 4-6 May 2015, Taipei, (2015) 1-4, doi: 10.1109/ISNE.2015.7131965.
- [6] Shyama M., Swaminathan P. “Digital linear and nonlinear controllers for buck converter”, International Journal of Soft Computing and Engineering 2(1) (2012) 336-342, Retrieval Number: A0447022112/2012©BEIESP.
- [7] Sonmez Y., Ayyıldız O., Kahraman H.T., Guvenc U., Duman S. “Improvement of buck converter performance using Artificial Bee Colony optimized-PID controller”, Journal of Automation and Control Engineering 3(4), (2015) 304-310, doi: 10.12720/joace.3.4.304-310.
- [8] Hekimoğlu B., Ekinci S. “Optimally Designed PID Controller for a DC-DC Buck Converter via a Hybrid Whale Optimization Algorithm with Simulated Annealing”, Electrica 20(1) (2020) 19-27, doi: 10.5152/electrica.2020.19034.
- [9] Sucu H., Goktas T., Arkan M. “Design, Simulation and Application of Buck Converter with Digital PI Controller”, Balkan Journal Of Electrical & Computer Engineering 9(2) (2021) 106-112, doi: 10.17694/bajece.884290.
- [10] Çimen, M.E., Garip, Z.B., Boz, A.F. “Chaotic flower pollination algorithm based optimal PID controller design for a buck converter”, Analog Integrated Circuits and Signal Processing 107(2021) 281–298, doi: 10.1007/s10470-020-01751-5.
- [11] Wang B., Yang, J., Jiao H.N., Zhu K., Chen Y.Q. “Design of auto disturbance rejection controller for train traction control system based on artificial bee colony algorithm”, Measurement, 160(2020) 107812, doi: 10.1016/j.measurement.2020.107812.
- [12] Sultan. G.A., Jarjes M.K. “Optimal PID controller design using artificial bee colony algorithm for robot arm”, Indonesian Journal of Electrical Engineering and Computer Science 21(1)(2021) 84-91, doi: 10.11591/ijeecs.v21.i1.pp84-91.
- [13] Ghosh A., Ray A.K., Nurujjaman Md., Jamshidi M. “Voltage and frequency control in conventional and PV integrated power systems by a particle swarm optimized Ziegler–Nichols based PID controller”, SN Applied Sciences, 3(2021)314, doi: 10.1007/s42452-021-04327-8.
- [14] Goud H., Swarnkar P. “Investigations on Metaheuristic algorithm for designing adaptive PID controller for continuous stirred tank reactor”, MAPAN-Journal of Metrology Society of India 34(1) (2019) 113–119, doi: 10.1007/s12647-018-00300-w.
- [15] Chen S.Y., Chen C.S., Yang Z.W. “Self-tuning cross-coupled two degree-of-freedom PID control for position synchronization of dual linear motors”, Applied Mathematical Modelling 64(2018) 214–234, doi: 10.1016/j.apm.2018.07.020.
- [16] Gözde H., Taplamacioglu M.C., Kocaarslan İ. “Comparative performance analysis of Artificial Bee Colony algorithm in automatic generation control for interconnected reheat thermal power system”, Electrical Power and Energy Systems 42 (2012) 167–178, doi: 10.1016/j.ijepes.2012.03.039.
- [17] El-Telbany M.E. “Tuning PID Controller for DC Motor: An Artificial Bees Optimization Approach”, International Journal of Computer Applications 77(15) (2013) 18-21, doi: 10.5120/13559-1341.
- [18] Sharma A., Aharma A.,Choudhary S., Pachauri R.K., Shrivastava A., Kumar D. “A Review on Artificial Bee Colony and it’s Engineering Applications”, Journal of Critical Reviews 7(11)(2020) 4097-4107, doi: 10.31838/jcr.07.11.558.
- [19] Kazimierczuk M. K. “Pulse-Width Modulated DC-DC power converters”, John Wiley & Sons, UK, 2008.
- [20] Singh N.S., Khandelwal C.S. “Modelling and digitized discrete feedback loop with PID compensator for buck converter using MATLAB/Simulink”, International Conference on Power, Automation and Communication (INPAC), (2014) 55-59, 6-8 October 2014, Amravati, doi: 10.1109/INPAC.2014.6981135.
- [21] Altinoz O.T., Erdem H. “Evaluation Function Comparison of Particle Swarm Optimization for Buck Converter”, International Symposium on Power Electronics Electrical Drives Automation and Motion (SPEEDAM), (2010) 798-802, 4-16 June 2010, Pisa, doi: 10.1109/ICCCI.2012.6158919.
- [22] Karaboga, D. "An ideal based on honey bee swarm for numerical optimization", Technical Report – TR06, Erciyes University, Engineering Faculty, Computer Engineering Department, October 2005.
- [23] Karaboga D., Akay B. "A comparative study of artificial bee colony algorithm", Applied Mathematics and Computation, 214(1) (2009) 108-132, doi:10.1016/j.amc.2009.03.090.
- [24] Karaboga D., Basturk B. "A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm", Journal of Global Optimization, 39(3) (2007) 459-471, doi: 10.1007/s10898-007-9149-x.
- [25] Demircan C., Bayrakçı H.C., Keçebaş A. “Machine Learning-based improvement of empiric models for an accurate estimating process of global solar radiation”, Sustainable Energy Technologies and Assessments, 37(2020) 100574, doi: 10.1016/j.seta.2019.100574.
- [26] Özkaraca O., Keçebaş A., Demircan C. “Comparative thermodynamic evaluation of a geothermal power plant by using the advanced exergy and artificial bee colony methods”, Energy, 156(2018) 169-180, doi: 10.1016/j.energy.2018.05.095