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Otomatik Gerilim Regülatörü Sistemi Denetleyici Tasarımı için Meta-Sezgisel Algoritmaların Performansı

Yıl 2024, Cilt: 14 Sayı: 4, 2258 - 2289, 15.12.2024
https://doi.org/10.31466/kfbd.1558173

Öz

Senkron generatörlerin terminal gerilimlerinin ayarlanması otomatik gerilim regülatörleri (AVR) tarafından sağlanır. Terminal geriliminin istenilen diğer bir deyişle referans gerilimde tutulması için sistemdeki değişikliklere hızlıca tepki verebilen bir denetleyici tarafından terminal gerilimin kontrol edilmesi gereklidir. Kullanılacak denetleyicinin seçimi önemli olduğu kadar parametrelerin ayarı da önemlidir. Bu sebeple çalışmada AVR sistemi için farklı denetleyici tiplerinin parametreleri farklı optimizasyon algoritmaları ve farklı amaç fonksiyonları kullanılarak optimize edilmiştir. Bu sayede optimizasyon algoritmalarının aynı koşullarda farklı durumlar altında performansları ortaya koyulmuştur. AVR sisteminde kullanılan denetleyiciler oransal-integral-türevsel denetleyici (PID), kesir dereceli PID (FOPID) ve FOPID denetleyicisine ek ikinci türev operatörü içeren versiyonu FOPIDD kullanılmaktadır. Bu denetleyicilerin parametreleri zebra optimizasyon algoritması (ZOA), karahindiba optimizasyon algoritması (DO) ve çiçek tozlaşma optimizasyon algoritması (FPA) ile optimize edilmiştir. Optimizasyon sürecinde ise zaman ağırlıklı mutlak hatanın integrali (ITAE) ve hata tabanlı yaklaşıma karşı olarak oluşturulan Zwe-Lee Gaing (ZLG) amaç fonksiyonları kullanılmıştır. Elde edilen denetleyici-amaç fonksiyonu-algoritma performansları zaman bölge analizi, yakınsama eğrisi, kutu grafikleri ve diğer istatistiksel yöntemler ile karşılaştırılmıştır.

Kaynakça

  • Altbawi, S. M. A., Mokhtar, A. S. Bin, Jumani, T. A., Khan, I., Hamadneh, N. N., & Khan, A. (2024). Optimal design of Fractional order PID controller based Automatic voltage regulator system using gradient-based optimization algorithm. Journal of King Saud University - Engineering Sciences, 36(1). https://doi.org/10.1016/j.jksues.2021.07.009
  • Ayas, M. S., & Sahin, E. (2021). FOPID controller with fractional filter for an automatic voltage regulator. Computers and Electrical Engineering, 90. https://doi.org/10.1016/j.compeleceng.2020.106895
  • Bhookya, J., & Jatoth, R. K. (2020). Improved Jaya algorithm-based FOPID/PID for AVR system. COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 39(4). https://doi.org/10.1108/COMPEL-08-2019-0319
  • Bhullar, A. K., Kaur, R., & Sondhi, S. (2020). Enhanced crow search algorithm for AVR optimization. Soft Computing, 24(16). https://doi.org/10.1007/s00500-019-04640-w
  • Bingul, Z., & Karahan, O. (2018). A novel performance criterion approach to optimum design of PID controller using cuckoo search algorithm for AVR system. Journal of the Franklin Institute, 355(13). https://doi.org/10.1016/j.jfranklin.2018.05.056
  • Blondin, M. J., Sicard, P., & Pardalos, P. M. (2019). Controller Tuning Approach with robustness, stability and dynamic criteria for the original AVR System. Mathematics and Computers in Simulation, 163. https://doi.org/10.1016/j.matcom.2019.02.019
  • Can, Ö., Andiç, C., Ekinci, S., & Izci, D. (2023). Enhancing transient response performance of automatic voltage regulator system by using a novel control design strategy. Electrical Engineering, 105(4). https://doi.org/10.1007/s00202-023-01777-8
  • Cavdar, B., Dincer, K., Baslik, S., Sahin, E. ¸, & Nuroglu, F. M. (2023). A novel objective function design and detailed analysis for the AVR-LFC system. Springer India, 4(48), 229. https://doi.org/10.1007/s12046-023-02292-zS
  • Çavdar, B., Şahin, E., Akyazı, Ö., & Nuroğlu, F. M. (2023). A novel optimal PIλ1Iλ2Dμ1Dμ2 controller using mayfly optimization algorithm for automatic voltage regulator system. Neural Computing and Applications, 35(27). https://doi.org/10.1007/s00521-023-08834-0
  • Çelik, E. (2021). Design of new fractional order PI–fractional order PD cascade controller through dragonfly search algorithm for advanced load frequency control of power systems. Soft Computing, 25(2). https://doi.org/10.1007/s00500-020-05215-w
  • Danell, K. , Bergström, R. , & Duncon, P. ,& P. J. (2006). Large herbivore ecology ecosystem dynamics and conservation. Choice Reviews Online, 44(04). https://doi.org/10.5860/choice.44-2102
  • Dhanasekaran, B., Siddhan, S., & Kaliannan, J. (2020). Ant colony optimization technique tuned controller for frequency regulation of single area nuclear power generating system. Microprocessors and Microsystems, 73. https://doi.org/10.1016/j.micpro.2019.102953
  • Dogruer, T., & Can, M. S. (2022). Design and robustness analysis of fuzzy PID controller for automatic voltage regulator system using genetic algorithm. Transactions of the Institute of Measurement and Control, 44(9). https://doi.org/10.1177/01423312211066758
  • Ekinci, S., & Hekimoglu, B. (2019). Improved Kidney-Inspired Algorithm Approach for Tuning of PID Controller in AVR System. IEEE Access, 7. https://doi.org/10.1109/ACCESS.2019.2906980
  • El-Deen, A. T., Hakim Mahmoud, A. A., & El-Sawi, A. R. (2015). Optimal PID tuning for DC motor speed controller based on genetic algorithm. International Review of Automatic Control, 8(1). https://doi.org/10.15866/ireaco.v8i1.4839
  • Eltag, K., & Zhang, B. (2021). Design Robust Self-tuning FPIDF Controller for AVR System. International Journal of Control, Automation and Systems, 19(2). https://doi.org/10.1007/s12555-019-1071-8
  • Gaing, Z. L. (2004). A particle swarm optimization approach for optimum design of PID controller in AVR system. IEEE Transactions on Energy Conversion, 19(2). https://doi.org/10.1109/TEC.2003.821821
  • Ghosh, A., Ray, A. K., Nurujjaman, M., & Jamshidi, M. (2021). 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(3). https://doi.org/10.1007/s42452-021-04327-8
  • Gozde, H. (2020). Robust 2DOF state-feedback PI-controller based on meta-heuristic optimization for automatic voltage regulation system. ISA Transactions, 98. https://doi.org/10.1016/j.isatra.2019.08.056
  • Güvenç, U., Yiǧit, T., Işik, A. H., & Akkaya, I. (2016). Performance analysis of biogeography-based optimization for automatic voltage regulator system. Turkish Journal of Electrical Engineering and Computer Sciences, 24(3). https://doi.org/10.3906/elk-1311-111
  • Jumani, T. A., Mustafa, M. W., Hussain, Z., Md. Rasid, M., Saeed, M. S., Memon, M. M., Khan, I., & Nisar, K. S. (2020). Jaya optimization algorithm for transient response and stability enhancement of a fractional-order PID based automatic voltage regulator system. Alexandria Engineering Journal, 59(4). https://doi.org/10.1016/j.aej.2020.03.005
  • Khan, I. A., Alghamdi, A. S., Jumani, T. A., Alamgir, A., Awan, A. B., & Khidrani, A. (2019). Salp swarm optimization algorithm-based fractional order pid controller for dynamic response and stability enhancement of an automatic voltage regulator system. Electronics (Switzerland), 8(12). https://doi.org/10.3390/electronics8121472
  • Kose, E. (2020). Optimal Control of AVR System with Tree Seed Algorithm-Based PID Controller. IEEE Access, 8. https://doi.org/10.1109/ACCESS.2020.2993628
  • Kundur, P., Paserba, J., Ajjarapu, V., Andersson, G., Bose, A., Canizares, C., Hatziargyriou, N., Hill, D., Stankovic, A., Taylor, C., Van Cursem, T., & Vittal, V. (2004). Definition and classification of power system stability. IEEE Transactions on Power Systems, 19(3). https://doi.org/10.1109/TPWRS.2004.825981
  • Micev, M., Ćalasan, M., & Oliva, D. (2020). Fractional order PID controller design for an AVR system using Chaotic Yellow Saddle Goatfish Algorithm. Mathematics, 8(7). https://doi.org/10.3390/math8071182
  • Mosaad, A. M., Attia, M. A., & Abdelaziz, A. Y. (2018). Comparative Performance Analysis of AVR Controllers Using Modern Optimization Techniques. Electric Power Components and Systems, 46(19–20). https://doi.org/10.1080/15325008.2018.1532471
  • Moschos, I., & Parisses, C. (2022). A novel optimal PIλDND2N2 controller using coyote optimization algorithm for an AVR system. Engineering Science and Technology, an International Journal, 26. https://doi.org/10.1016/j.jestch.2021.04.010
  • Oustaloup, A., Levron, F., Mathieu, B., & Nanot, F. M. (2000). Frequency-band complex noninteger differentiator: Characterization and synthesis. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 47(1). https://doi.org/10.1109/81.817385
  • Paliwal, N., Srivastava, L., & Pandit, M. (2021). Equilibrium optimizer tuned novel FOPID-DN controller for automatic voltage regulator system. International Transactions on Electrical Energy Systems, 31(8). https://doi.org/10.1002/2050-7038.12930
  • Saadat, H. (1999). Power system analysis (Vol. 2).
  • Sahib, M. A. (2015a). A novel optimal PID plus second order derivative controller for AVR system. Engineering Science and Technology, an International Journal, 18(2). https://doi.org/10.1016/j.jestch.2014.11.006
  • Sahib, M. A. (2015b). Engineering Science and Technology , an International Journal A novel optimal PID plus second order derivative controller for AVR system. Engineering Science and Technology, an International Journal, 18(2).
  • Sikander, A., & Thakur, P. (2020). A new control design strategy for automatic voltage regulator in power system. ISA Transactions, 100. https://doi.org/10.1016/j.isatra.2019.11.031
  • Tabak, A. (2021a). A novel fractional order PID plus derivative (PIλDµDµ2) controller for AVR system using equilibrium optimizer. COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering. https://doi.org/10.1108/COMPEL-02-2021-0044
  • Tabak, A. (2021b). Maiden application of fractional order PID plus second order derivative controller in automatic voltage regulator. International Transactions on Electrical Energy Systems, 31(12). https://doi.org/10.1002/2050-7038.13211
  • Trojovska, E., Dehghani, M., & Trojovsky, P. (2022). Zebra Optimization Algorithm: A New Bio-Inspired Optimization Algorithm for Solving Optimization Algorithm. IEEE Access, 10. https://doi.org/10.1109/ACCESS.2022.3172789
  • Wilson, A. M., Hubel, T. Y., Wilshin, S. D., Lowe, J. C., Lorenc, M., Dewhirst, O. P., Bartlam-Brooks, H. L. A., Diack, R., Bennitt, E., Golabek, K. A., McNutt, J. W., Curtin, N. A., & West, T. G. (2018). Biomechanics of predator-prey arms race in lion, zebra, cheetah and impala. Nature, 554(7691). https://doi.org/10.1038/nature25479
  • Xue, D., Zhao, C., & Chen, Y. Q. (2006). A modified approximation method of fractional order system. 2006 IEEE International Conference on Mechatronics and Automation, ICMA 2006, 2006. https://doi.org/10.1109/ICMA.2006.257769
  • Yang, X. S. (2012). Flower pollination algorithm for global optimization. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7445 LNCS. https://doi.org/10.1007/978-3-642-32894-7_27
  • Zeng, G. Q., Chen, J., Dai, Y. X., Li, L. M., Zheng, C. W., & Chen, M. R. (2015). Design of fractional order PID controller for automatic regulator voltage system based on multi-objective extremal optimization. Neurocomputing, 160. https://doi.org/10.1016/j.neucom.2015.02.051
  • Zhao, S., Zhang, T., Ma, S., & Chen, M. (2022). Dandelion Optimizer: A nature-inspired metaheuristic algorithm for engineering applications. Engineering Applications of Artificial Intelligence, 114. https://doi.org/10.1016/j.engappai.2022.105075
  • Zhou, G., Li, J., Tang, Z., Luo, Q., & Zhou, Y. (2020). An improved spotted hyena optimizer for PID parameters in an AVR system. Mathematical Biosciences and Engineering, 17(4). https://doi.org/10.3934/MBE.2020211

Performance of Meta-Heuristic Algorithms for Automatic Voltage Regulatör System Controller Design

Yıl 2024, Cilt: 14 Sayı: 4, 2258 - 2289, 15.12.2024
https://doi.org/10.31466/kfbd.1558173

Öz

The terminal voltage of synchronous generators is regulated by automatic voltage regulators (AVR). In order to maintain the terminal voltage at the desired, i.e. reference voltage, it is necessary to control the terminal voltage, it is necessary to control the terminal voltage by a controller that can react quickly to changes in the system. The choice of the controller to be used is as important as the setting of the parameters. For this reason, the parameters of different controller types fort he AVR system are optimized using different optimization algorithms and different objective functions. In this way, the performance of the optimization algorithms under different situations under the same conditions was demonstrated. The controllers used in the AVR system are proportional-integral-derivative controller (PID), fractional-order PID (FOPID) and FOPIDD, a version of the FOPID controller with an additional second derivative operator. The parameters of these controllers were optimized with the zebra optimization algorithm (ZOA), dandelion optimization algorithm (DO) and flower pollination optimization algorithm (FPA). In the optimization provess, the time-domain integral of absolute error (ITAE) and Zwe-Lee Gaing (ZLG) objective functions, which are constructed as opposed to the error-based approach are used. The optained controller-purpose function-algorithm performances are compared with time domain analysis, convergence curve, box plots and other statistical methods.

Kaynakça

  • Altbawi, S. M. A., Mokhtar, A. S. Bin, Jumani, T. A., Khan, I., Hamadneh, N. N., & Khan, A. (2024). Optimal design of Fractional order PID controller based Automatic voltage regulator system using gradient-based optimization algorithm. Journal of King Saud University - Engineering Sciences, 36(1). https://doi.org/10.1016/j.jksues.2021.07.009
  • Ayas, M. S., & Sahin, E. (2021). FOPID controller with fractional filter for an automatic voltage regulator. Computers and Electrical Engineering, 90. https://doi.org/10.1016/j.compeleceng.2020.106895
  • Bhookya, J., & Jatoth, R. K. (2020). Improved Jaya algorithm-based FOPID/PID for AVR system. COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 39(4). https://doi.org/10.1108/COMPEL-08-2019-0319
  • Bhullar, A. K., Kaur, R., & Sondhi, S. (2020). Enhanced crow search algorithm for AVR optimization. Soft Computing, 24(16). https://doi.org/10.1007/s00500-019-04640-w
  • Bingul, Z., & Karahan, O. (2018). A novel performance criterion approach to optimum design of PID controller using cuckoo search algorithm for AVR system. Journal of the Franklin Institute, 355(13). https://doi.org/10.1016/j.jfranklin.2018.05.056
  • Blondin, M. J., Sicard, P., & Pardalos, P. M. (2019). Controller Tuning Approach with robustness, stability and dynamic criteria for the original AVR System. Mathematics and Computers in Simulation, 163. https://doi.org/10.1016/j.matcom.2019.02.019
  • Can, Ö., Andiç, C., Ekinci, S., & Izci, D. (2023). Enhancing transient response performance of automatic voltage regulator system by using a novel control design strategy. Electrical Engineering, 105(4). https://doi.org/10.1007/s00202-023-01777-8
  • Cavdar, B., Dincer, K., Baslik, S., Sahin, E. ¸, & Nuroglu, F. M. (2023). A novel objective function design and detailed analysis for the AVR-LFC system. Springer India, 4(48), 229. https://doi.org/10.1007/s12046-023-02292-zS
  • Çavdar, B., Şahin, E., Akyazı, Ö., & Nuroğlu, F. M. (2023). A novel optimal PIλ1Iλ2Dμ1Dμ2 controller using mayfly optimization algorithm for automatic voltage regulator system. Neural Computing and Applications, 35(27). https://doi.org/10.1007/s00521-023-08834-0
  • Çelik, E. (2021). Design of new fractional order PI–fractional order PD cascade controller through dragonfly search algorithm for advanced load frequency control of power systems. Soft Computing, 25(2). https://doi.org/10.1007/s00500-020-05215-w
  • Danell, K. , Bergström, R. , & Duncon, P. ,& P. J. (2006). Large herbivore ecology ecosystem dynamics and conservation. Choice Reviews Online, 44(04). https://doi.org/10.5860/choice.44-2102
  • Dhanasekaran, B., Siddhan, S., & Kaliannan, J. (2020). Ant colony optimization technique tuned controller for frequency regulation of single area nuclear power generating system. Microprocessors and Microsystems, 73. https://doi.org/10.1016/j.micpro.2019.102953
  • Dogruer, T., & Can, M. S. (2022). Design and robustness analysis of fuzzy PID controller for automatic voltage regulator system using genetic algorithm. Transactions of the Institute of Measurement and Control, 44(9). https://doi.org/10.1177/01423312211066758
  • Ekinci, S., & Hekimoglu, B. (2019). Improved Kidney-Inspired Algorithm Approach for Tuning of PID Controller in AVR System. IEEE Access, 7. https://doi.org/10.1109/ACCESS.2019.2906980
  • El-Deen, A. T., Hakim Mahmoud, A. A., & El-Sawi, A. R. (2015). Optimal PID tuning for DC motor speed controller based on genetic algorithm. International Review of Automatic Control, 8(1). https://doi.org/10.15866/ireaco.v8i1.4839
  • Eltag, K., & Zhang, B. (2021). Design Robust Self-tuning FPIDF Controller for AVR System. International Journal of Control, Automation and Systems, 19(2). https://doi.org/10.1007/s12555-019-1071-8
  • Gaing, Z. L. (2004). A particle swarm optimization approach for optimum design of PID controller in AVR system. IEEE Transactions on Energy Conversion, 19(2). https://doi.org/10.1109/TEC.2003.821821
  • Ghosh, A., Ray, A. K., Nurujjaman, M., & Jamshidi, M. (2021). 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(3). https://doi.org/10.1007/s42452-021-04327-8
  • Gozde, H. (2020). Robust 2DOF state-feedback PI-controller based on meta-heuristic optimization for automatic voltage regulation system. ISA Transactions, 98. https://doi.org/10.1016/j.isatra.2019.08.056
  • Güvenç, U., Yiǧit, T., Işik, A. H., & Akkaya, I. (2016). Performance analysis of biogeography-based optimization for automatic voltage regulator system. Turkish Journal of Electrical Engineering and Computer Sciences, 24(3). https://doi.org/10.3906/elk-1311-111
  • Jumani, T. A., Mustafa, M. W., Hussain, Z., Md. Rasid, M., Saeed, M. S., Memon, M. M., Khan, I., & Nisar, K. S. (2020). Jaya optimization algorithm for transient response and stability enhancement of a fractional-order PID based automatic voltage regulator system. Alexandria Engineering Journal, 59(4). https://doi.org/10.1016/j.aej.2020.03.005
  • Khan, I. A., Alghamdi, A. S., Jumani, T. A., Alamgir, A., Awan, A. B., & Khidrani, A. (2019). Salp swarm optimization algorithm-based fractional order pid controller for dynamic response and stability enhancement of an automatic voltage regulator system. Electronics (Switzerland), 8(12). https://doi.org/10.3390/electronics8121472
  • Kose, E. (2020). Optimal Control of AVR System with Tree Seed Algorithm-Based PID Controller. IEEE Access, 8. https://doi.org/10.1109/ACCESS.2020.2993628
  • Kundur, P., Paserba, J., Ajjarapu, V., Andersson, G., Bose, A., Canizares, C., Hatziargyriou, N., Hill, D., Stankovic, A., Taylor, C., Van Cursem, T., & Vittal, V. (2004). Definition and classification of power system stability. IEEE Transactions on Power Systems, 19(3). https://doi.org/10.1109/TPWRS.2004.825981
  • Micev, M., Ćalasan, M., & Oliva, D. (2020). Fractional order PID controller design for an AVR system using Chaotic Yellow Saddle Goatfish Algorithm. Mathematics, 8(7). https://doi.org/10.3390/math8071182
  • Mosaad, A. M., Attia, M. A., & Abdelaziz, A. Y. (2018). Comparative Performance Analysis of AVR Controllers Using Modern Optimization Techniques. Electric Power Components and Systems, 46(19–20). https://doi.org/10.1080/15325008.2018.1532471
  • Moschos, I., & Parisses, C. (2022). A novel optimal PIλDND2N2 controller using coyote optimization algorithm for an AVR system. Engineering Science and Technology, an International Journal, 26. https://doi.org/10.1016/j.jestch.2021.04.010
  • Oustaloup, A., Levron, F., Mathieu, B., & Nanot, F. M. (2000). Frequency-band complex noninteger differentiator: Characterization and synthesis. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 47(1). https://doi.org/10.1109/81.817385
  • Paliwal, N., Srivastava, L., & Pandit, M. (2021). Equilibrium optimizer tuned novel FOPID-DN controller for automatic voltage regulator system. International Transactions on Electrical Energy Systems, 31(8). https://doi.org/10.1002/2050-7038.12930
  • Saadat, H. (1999). Power system analysis (Vol. 2).
  • Sahib, M. A. (2015a). A novel optimal PID plus second order derivative controller for AVR system. Engineering Science and Technology, an International Journal, 18(2). https://doi.org/10.1016/j.jestch.2014.11.006
  • Sahib, M. A. (2015b). Engineering Science and Technology , an International Journal A novel optimal PID plus second order derivative controller for AVR system. Engineering Science and Technology, an International Journal, 18(2).
  • Sikander, A., & Thakur, P. (2020). A new control design strategy for automatic voltage regulator in power system. ISA Transactions, 100. https://doi.org/10.1016/j.isatra.2019.11.031
  • Tabak, A. (2021a). A novel fractional order PID plus derivative (PIλDµDµ2) controller for AVR system using equilibrium optimizer. COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering. https://doi.org/10.1108/COMPEL-02-2021-0044
  • Tabak, A. (2021b). Maiden application of fractional order PID plus second order derivative controller in automatic voltage regulator. International Transactions on Electrical Energy Systems, 31(12). https://doi.org/10.1002/2050-7038.13211
  • Trojovska, E., Dehghani, M., & Trojovsky, P. (2022). Zebra Optimization Algorithm: A New Bio-Inspired Optimization Algorithm for Solving Optimization Algorithm. IEEE Access, 10. https://doi.org/10.1109/ACCESS.2022.3172789
  • Wilson, A. M., Hubel, T. Y., Wilshin, S. D., Lowe, J. C., Lorenc, M., Dewhirst, O. P., Bartlam-Brooks, H. L. A., Diack, R., Bennitt, E., Golabek, K. A., McNutt, J. W., Curtin, N. A., & West, T. G. (2018). Biomechanics of predator-prey arms race in lion, zebra, cheetah and impala. Nature, 554(7691). https://doi.org/10.1038/nature25479
  • Xue, D., Zhao, C., & Chen, Y. Q. (2006). A modified approximation method of fractional order system. 2006 IEEE International Conference on Mechatronics and Automation, ICMA 2006, 2006. https://doi.org/10.1109/ICMA.2006.257769
  • Yang, X. S. (2012). Flower pollination algorithm for global optimization. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7445 LNCS. https://doi.org/10.1007/978-3-642-32894-7_27
  • Zeng, G. Q., Chen, J., Dai, Y. X., Li, L. M., Zheng, C. W., & Chen, M. R. (2015). Design of fractional order PID controller for automatic regulator voltage system based on multi-objective extremal optimization. Neurocomputing, 160. https://doi.org/10.1016/j.neucom.2015.02.051
  • Zhao, S., Zhang, T., Ma, S., & Chen, M. (2022). Dandelion Optimizer: A nature-inspired metaheuristic algorithm for engineering applications. Engineering Applications of Artificial Intelligence, 114. https://doi.org/10.1016/j.engappai.2022.105075
  • Zhou, G., Li, J., Tang, Z., Luo, Q., & Zhou, Y. (2020). An improved spotted hyena optimizer for PID parameters in an AVR system. Mathematical Biosciences and Engineering, 17(4). https://doi.org/10.3934/MBE.2020211
Toplam 42 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Elektrik Mühendisliği (Diğer)
Bölüm Makaleler
Yazarlar

Ömer Öztürk 0000-0003-3341-6419

Bora Çavdar 0000-0002-0545-2925

Yayımlanma Tarihi 15 Aralık 2024
Gönderilme Tarihi 30 Eylül 2024
Kabul Tarihi 11 Aralık 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 14 Sayı: 4

Kaynak Göster

APA Öztürk, Ö., & Çavdar, B. (2024). Otomatik Gerilim Regülatörü Sistemi Denetleyici Tasarımı için Meta-Sezgisel Algoritmaların Performansı. Karadeniz Fen Bilimleri Dergisi, 14(4), 2258-2289. https://doi.org/10.31466/kfbd.1558173