Page 187 - IJOCTA-15-1
P. 187
Recent metaheuristics on control parameter determination
[17] Dash, P., Saikia, L. C., & Sinha, N. (2015). Com- [29] Wang, L., Cao, Q., Zhang, Z., Mirjalili, S., &
parison of performances of several FACTS de- Zhao, W. (2022). Artificial rabbits optimization:
vices using Cuckoo search algorithm optimized A new bio-inspired meta-heuristic algorithm for
2DOF controllers in multi-area AGC. Interna- solving engineering optimization problems. En-
tional Journal of Electrical Power & Energy Sys- gineering Applications of Artificial Intelligence,
tems, 65, 316-324. 114, 105082.
[18] Dash, P., Saikia, L. C., & Sinha, N. (2015). Au- [30] Chopra, N., & Ansari, M. M. (2022). Golden
tomatic generation control of multi area thermal jackal optimization: A novel nature-inspired op-
system using Bat algorithm optimized PD–PID timizer for engineering applications. Expert Sys-
cascade controller. International Journal of Elec- tems with Applications, 198, 116924.
trical Power & Energy Systems, 68, 364-372. [31] Agushaka, J. O., Ezugwu, A. E., & Abualigah, L.
[19] Puangdownreong, D., Nawikavatan, A., & Tham- (2023). Gazelle optimization algorithm: a novel
marat, C. (2016). Optimal design of I-PD con- nature-inspired metaheuristic optimizer. Neural
troller for DC motor speed control system by Computing and Applications, 35(5), 4099-4131.
cuckoo search. Procedia Computer Science, 86, [32] Trojovsk´y, P., & Dehghani, M. (2022). Pelican
83-86. optimization algorithm: A novel nature-inspired
[20] Sahoo, B. P., & Panda, S. (2018). Improved grey algorithm for engineering applications. Sensors,
wolf optimization technique for fuzzy aided PID 22(3), 855.
controller design for power system frequency con- [33] Askarzadeh, A. (2016). A novel metaheuristic
trol. Sustainable Energy, Grids and Networks, 16, method for solving constrained engineering opti-
278-299. mization problems: crow search algorithm. Com-
[21] Wang, L., Ni, H., Zhou, W., Pardalos, P. M., puters & structures, 169, 1-12.
Fang, J., & Fei, M. (2014). MBPOA-based LQR [34] Mirjalili, S., & Lewis, A. (2016). The whale opti-
controller and its application to the double- mization algorithm. Advances in engineering soft-
parallel inverted pendulum system. Engineering ware, 95, 51-67.
Applications of Artificial Intelligence, 36, 262- [35] Mirjalili, S., Mirjalili, S. M., & Lewis, A. (2014).
268. Grey wolf optimizer. Advances in engineering
[22] Demirta¸s, M., & Ahmad, F. (2023). Fractional software, 69, 46-61.
fuzzy PI controller using particle swarm opti- [36] Yang, X. S. (2012, September). Flower pollina-
mization to improve power factor by boost con- tion algorithm for global optimization. In Inter-
verter. An International Journal of Optimization national conference on unconventional computing
and Control: Theories & Applications (IJOCTA). and natural computation (pp. 240-249). Berlin,
¨
[23] Ozyetkin, M. M., & Birdane, H. (2023). The pro- Heidelberg: Springer Berlin Heidelberg.
cesses with fractional order delay and PI con- [37] Hansen, N. (2016). The CMA evolution strategy:
troller design using particle swarm optimization. A tutorial. arXiv preprint arXiv:1604.00772.
An International Journal of Optimization and [38] Olmez, Y., Koca, G. O., & Akpolat, Z. H. (2022).
Control: Theories & Applications (IJOCTA), Clonal selection algorithm based control for two-
13(1), 81-91. wheeled self-balancing mobile robot. Simulation
[24] Askari, Q., Younas, I., & Saeed, M. (2020). Po- Modelling Practice and Theory, 118, 102552.
litical Optimizer: A novel socio-inspired meta- [39] Sharma, A., & Singh, N. (2024). Load fre-
heuristic for global optimization. Knowledge- quency control of connected multi-area multi-
based systems, 195, 105709. source power systems using energy storage and
[25] Faramarzi, A., Heidarinejad, M., Stephens, B., lyrebird optimization algorithm tuned PID con-
& Mirjalili, S. (2020). Equilibrium optimizer: A troller. Journal of Energy Storage, 100, 113609.
novel optimization algorithm. Knowledge-based [40] Ozmen Koca, G., & Korkmaz, D. (2019). Neural
systems, 191, 105190. network based control of a two-mass drive system.
[26] Abualigah, L., Yousri, D., Abd Elaziz, M., Ewees, International Journal of Intelligent Systems and
A. A., Al-Qaness, M. A., & Gandomi, A. H. Applications in Engineering, 7(2), 92-98.
(2021). Aquila optimizer: a novel meta-heuristic
optimization algorithm. Computers & Industrial
Engineering, 157, 107250. Yagmur Olmez earned her M.Sc. and Ph.D. degrees
[27] Karami, H., Anaraki, M. V., Farzin, S., & Mir- in Mechatronics Engineering from the Institute of Sci-
jalili, S. (2021). Flow direction algorithm (FDA): ence at Firat University, Elazig, Turkiye, in 2018 and
a novel optimization approach for solving opti- 2024, respectively. Currently, she is a Research Assis-
mization problems. Computers & Industrial En- tant in the Department of Mechatronics Engineering
gineering, 156, 107224. at the Faculty of Engineering, Nigde Omer Halisdemir
[28] Akbari, M. A., Zare, M., Azizipanah-Abarghooee, University. Her research interests encompass image
R., Mirjalili, S., & Deriche, M. (2022). The chee- processing, metaheuristic algorithms, artificial intel-
tah optimizer: A nature-inspired metaheuristic ligence, system modeling, and advanced control tech-
algorithm for large-scale optimization problems. niques.
Scientific reports, 12(1), 10953. https://orcid.org/0000-0002-1615-7390
181

