Araştırma Makalesi
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Performance Analysis of Marine Predators Algorithm for Automatic Voltage Regulator System

Yıl 2022, Cilt 6, Sayı 1, 53 - 64, 28.06.2022
https://doi.org/10.26650/acin.1026494

Öz

In this study, the emerging, novel marine predators algorithm is proposed to adjust the proportional–integral– derivative controller of the automatic voltage regulator system. With the proposed algorithm, this study aimed to minimize the maximum percent excess of the terminal voltage, settling time, rise time, and steady-state error and improve the transient response of the automatic voltage regulator system with an optimal proportional–integral– derivative controller. The integral of squared error, integral of weighted squared error, squared integral of time, and Zwe-Lee Gaing objective functions were used to set the controller parameters. The performance of the proportional–integral–derivative controller based on the marine predators algorithm was compared with those of the proportional–integral–derivative controllers adapted by different metaheuristic algorithms using various objective functions suggested in the literature. These analyses were conducted using analysis methods such as transient response, root locus, and robustness. The simulation results show better performance in terms of the settling time, over-peak, and stability of the proportional–integral–derivative-controlled automatic voltage regulator system tuned with the marine predators algorithm.

Kaynakça

  • Abdel-Basset, M., El-Shahat, D., Chakrabortty, R.K. & Ryan, M. (2021). Parameter estimation of photovoltaic models using an improved marine predators algorithm, Energy Conversion and Management, 227, 113491. https,//doi.org/10.1016/j.enconman.2020.113491. google scholar
  • Ayas, M.S. (2019). Design of an optimized fractional high-order differential feedback controller for an AVR system. Electrical Engineering, 101,1221-1233. https,//doi.org/10.1007/s00202-019-00842-5. google scholar
  • Bhookya, J., Jatoth, R. K. (2019). Optimal FOPID/PID controller parameters tuning for the AVR system based on sine-cosine-algorithm. Evolutionary Intelligence, 12,725-733.https,//doi.org/10.1007/s12065-019-00290-x. google scholar
  • Bhullar, A.K., Kaur, R. & Sondhi, S. (2020). Enhanced crow search algorithm for AVR optimization. Soft Computing, 24,11957-11987.https,//doi. org/10.1007/s00500-019-04640-w. google scholar
  • Bingul, Z., & Karahan, O. (2018). A novel performance criterion approach to optimumdesign of PID controller using cuckoo search algorithm for AVR system. Journal of the Franklin Institute, 355, 5534-5559. https,//doi.org/10.1016/j.jfranklin.2018.05.056 google scholar
  • Blondin, M., Sanchis, J., Sicard P. & Herrero J.M. (2018). New optimal controller tuning method for an AVR system using a simplifed Ant Colony Optimization with a new constrained Nelder-Mead algorithm. Appl Soft Comput ,62,216-229. https,//doi.org/10.1016/j.asoc.2017.10.007 google scholar
  • Blondin, M.J., Sanchis, J. Sicard, P. & Herrero, J.M. (2018). New optimal controller tuning method for an AVR system using a simplified Ant Colony Optimization with a new constrained Nelder-Mead algorithm. Applied Soft Computing, 62, 216-229. ttps,//doi.org/10.1016/j.asoc.2017.10.007. google scholar
  • Çelik, E. (2018). Incorporation of stochastic fractal search algorithm into efficient design of PID controller for an automatic voltage regulator system. Neural Computing and Applications, 30,1991-2002. https,//doi.org/10.1007/s00521-017-3335-7. google scholar
  • Chen, X., Qi, X., Wang Z., Cui, C., Wu, B. & Yang Y. (2021) .Fault diagnosis of rolling bearing using marine predators algorithm-based support vector machine and topology learning and out-of-sample embedding. Measurement, 176,109116. https,//doi.org/10.1016/j.measurement.2021.109116. google scholar
  • Ekinci, S. & Hekimoğlu, B. (2019). Improved Kidney-Inspired Algorithm Approach for Tuning of PID Controller in AVR System. IEEE Access, 7, 21693536. http,//dx.doi.org/10.1109/ACCESS.2019.2906980. google scholar
  • Faramarzi, A., Heidarinejad, M., Mirjalili, S. & Gandomi, A. H. (2020). Marine predator algorithm, a nature-inspired metaheuristic. Int J Expert Syst Appl, 52, 113377. https,//doi.org/10.1016/j.eswa.2020.11337. google scholar
  • Faramarzi, A., Heidarinejad, M., Mirjalili, S. & Gandomi, A. H. (2020). Marine Predators Algorithm, A nature-inspired metaheuristic. Expert Systems With Applications, 152, 113377. https,//doi.org/10.1016/j.eswa.2020.113377. google scholar
  • Gaing, L. (2004). A particle swarm optimization approach for optimum design of PID controller in AVR system. IEEE Trans. Energy Convers., 19(2),384-391. https,//doi.org/10.1109/TEC.2003.821821 google scholar
  • Gozde, H., & Taplamacioglu, M.C. (2011). Comparative performance analysis of artificial bee colony algorithm for automatic voltage regülatör (AVR) system. Journal of the Franklin Institute, 348, 1927-1946. http,//dx.doi.org/10.1016/j.jfranklin.2011.05.012 google scholar
  • Guvenc, U., Yiğit, T., Işık, A.H. & Akkaya İ. (2016). Performance analysis of biogeography-based optimization for automatic voltage regulator system. google scholar Turk J Elec Eng & Comp Sci, 24, 1150 -1162. http,//dx.doi.org/10.3906/elk-1311-11. google scholar
  • Hekimoğlu, B. & Ekinci, S. (2018). Grasshopper Optimization Algorithm for Automatic Voltage Regulator System. 5th International Conference on Electrical and Electronics Engineering, 152-156. google scholar
  • Hekimoğlu, B. (2019). Sine-cosine algorithm-based optimization for automatic voltage regulator system. Transactions of the Institute of Measurement and Control, 41(6), 1761-1771. http,//dx.doi.org/10.1177/0142331218811453. google scholar
  • Li, Y., Ang, K.H. & Chong, G.C.Y. (2006). PID control system analysis and design. IEEE Control Systems Magazine, 26(1),32-41. https,//doi.org/10.1109/ TCST.2005.847331. google scholar Micev, M., Calasan, M., Ali, Z.M., Hasanien, H.M. & Aleem, S.H.E. A. (2021). Optimal design of automatic voltage regulation controller using hybrid simulated annealing - Manta ray foraging optimization algorithm. Ain Shams Engineering Journal, 12, 641-657. https,//doi.org/10.1016/j.asej.2020.07.010. google scholar
  • Mohanty, P.K., Sahu, B.K. & Sidhartha Panda (2014) Tuning and Assessment of Proportional-Integral-Derivative Controller for an Automatic Voltage Regulator System Employing Local Unimodal Sampling Algorithm. Electric Power Components and Systems, 42(9), 959-969. http,//dx.doi.org/10. 1080/15325008.2014.903546 google scholar
  • Panda, S., Sahub, B.K. & Mohanty, P.K. (2012). Design and performance analysis of PID controller for an automatic voltage regulator system using simplified particle swarm optimization. Journal of the Franklin Institute, 349, 2609-2625. http,//dx.doi.org/10.1016/j.jfranklin.2012.06.008 google scholar
  • Sahib, M.A. (2015). A novel optimal PID plus second order derivative controller for AVR system. Engineering Science and Technology an International Journal, 18(2), 194-206. https,//doi.org/10.1016/j.jestch.2014.11.006. google scholar
  • Yousri, D., Hasanien, H.M. & Fathy, A. (2021). Parameters identification of solid oxide fuel cell for static and dynamic simulation using comprehensive learning dynamic multi-swarm marine predators algorithm. Energy Conversion and Management, 228, 113692. https,//doi.org/10.1016/j. enconman.2020.113692. google scholar

Otomatik Gerilim Regülatör Sistemi için Deniz Yırtıcıları Algoritmasının Performans Analizi

Yıl 2022, Cilt 6, Sayı 1, 53 - 64, 28.06.2022
https://doi.org/10.26650/acin.1026494

Öz

Bu makalede otomatik gerilim regülatör sistemin oransal integral türev denetleyici optimal parametre değerlerini ayarlamak amacıyla yeni bir algoritma olan deniz yırtıcıları algoritması önerilmiştir. Önerilen algoritma ile terminal geriliminin maksimum yüzde aşımı, yerleşme süresi, yükselme süresi ve kararlı durum hatasını en aza indirmek ve optimal oransal integral türev denetleyicisi ile otomatik gerilim regülatör sisteminin geçici durum yanıtının iyileştirilmesi amaçlanmıştır. Denetleyici parametrelerini ayarlamak için karesel hatanın integrali, ağırlıklı karesel hatanın integrali, zaman’ın karesel integrali ve Zwe-Lee Gaing amaç fonksiyonları kullanılmıştır. Deniz yırtıcıları algoritma tabanlı oransal-integral-türev denetleyicinin performansı, literatürde önerilen çeşitli amaç fonksiyonları kullanılarak gerçekleştirilen farklı meta-sezgisel algoritmalar tarafından uyarlanmış oransal integral türev denetleyicileri ile karşılaştırmalı analizler yapılmıştır. Bu analizler geçici tepki analizi, kök konum analizi ve sağlamlık gibi analiz yöntemleri ile gerçekleştirilmiştir. Simülasyon sonuçları, deniz yırtıcıları algoritmasıyla ayarlanan oransal integral türev kontrollü otomatik gerilim regülatör sisteminin yerleşme süresi, tepe aşımı ve kararlılık açısından daha iyi performans gösterdiğini kanıtlamıştır.

Kaynakça

  • Abdel-Basset, M., El-Shahat, D., Chakrabortty, R.K. & Ryan, M. (2021). Parameter estimation of photovoltaic models using an improved marine predators algorithm, Energy Conversion and Management, 227, 113491. https,//doi.org/10.1016/j.enconman.2020.113491. google scholar
  • Ayas, M.S. (2019). Design of an optimized fractional high-order differential feedback controller for an AVR system. Electrical Engineering, 101,1221-1233. https,//doi.org/10.1007/s00202-019-00842-5. google scholar
  • Bhookya, J., Jatoth, R. K. (2019). Optimal FOPID/PID controller parameters tuning for the AVR system based on sine-cosine-algorithm. Evolutionary Intelligence, 12,725-733.https,//doi.org/10.1007/s12065-019-00290-x. google scholar
  • Bhullar, A.K., Kaur, R. & Sondhi, S. (2020). Enhanced crow search algorithm for AVR optimization. Soft Computing, 24,11957-11987.https,//doi. org/10.1007/s00500-019-04640-w. google scholar
  • Bingul, Z., & Karahan, O. (2018). A novel performance criterion approach to optimumdesign of PID controller using cuckoo search algorithm for AVR system. Journal of the Franklin Institute, 355, 5534-5559. https,//doi.org/10.1016/j.jfranklin.2018.05.056 google scholar
  • Blondin, M., Sanchis, J., Sicard P. & Herrero J.M. (2018). New optimal controller tuning method for an AVR system using a simplifed Ant Colony Optimization with a new constrained Nelder-Mead algorithm. Appl Soft Comput ,62,216-229. https,//doi.org/10.1016/j.asoc.2017.10.007 google scholar
  • Blondin, M.J., Sanchis, J. Sicard, P. & Herrero, J.M. (2018). New optimal controller tuning method for an AVR system using a simplified Ant Colony Optimization with a new constrained Nelder-Mead algorithm. Applied Soft Computing, 62, 216-229. ttps,//doi.org/10.1016/j.asoc.2017.10.007. google scholar
  • Çelik, E. (2018). Incorporation of stochastic fractal search algorithm into efficient design of PID controller for an automatic voltage regulator system. Neural Computing and Applications, 30,1991-2002. https,//doi.org/10.1007/s00521-017-3335-7. google scholar
  • Chen, X., Qi, X., Wang Z., Cui, C., Wu, B. & Yang Y. (2021) .Fault diagnosis of rolling bearing using marine predators algorithm-based support vector machine and topology learning and out-of-sample embedding. Measurement, 176,109116. https,//doi.org/10.1016/j.measurement.2021.109116. google scholar
  • Ekinci, S. & Hekimoğlu, B. (2019). Improved Kidney-Inspired Algorithm Approach for Tuning of PID Controller in AVR System. IEEE Access, 7, 21693536. http,//dx.doi.org/10.1109/ACCESS.2019.2906980. google scholar
  • Faramarzi, A., Heidarinejad, M., Mirjalili, S. & Gandomi, A. H. (2020). Marine predator algorithm, a nature-inspired metaheuristic. Int J Expert Syst Appl, 52, 113377. https,//doi.org/10.1016/j.eswa.2020.11337. google scholar
  • Faramarzi, A., Heidarinejad, M., Mirjalili, S. & Gandomi, A. H. (2020). Marine Predators Algorithm, A nature-inspired metaheuristic. Expert Systems With Applications, 152, 113377. https,//doi.org/10.1016/j.eswa.2020.113377. google scholar
  • Gaing, L. (2004). A particle swarm optimization approach for optimum design of PID controller in AVR system. IEEE Trans. Energy Convers., 19(2),384-391. https,//doi.org/10.1109/TEC.2003.821821 google scholar
  • Gozde, H., & Taplamacioglu, M.C. (2011). Comparative performance analysis of artificial bee colony algorithm for automatic voltage regülatör (AVR) system. Journal of the Franklin Institute, 348, 1927-1946. http,//dx.doi.org/10.1016/j.jfranklin.2011.05.012 google scholar
  • Guvenc, U., Yiğit, T., Işık, A.H. & Akkaya İ. (2016). Performance analysis of biogeography-based optimization for automatic voltage regulator system. google scholar Turk J Elec Eng & Comp Sci, 24, 1150 -1162. http,//dx.doi.org/10.3906/elk-1311-11. google scholar
  • Hekimoğlu, B. & Ekinci, S. (2018). Grasshopper Optimization Algorithm for Automatic Voltage Regulator System. 5th International Conference on Electrical and Electronics Engineering, 152-156. google scholar
  • Hekimoğlu, B. (2019). Sine-cosine algorithm-based optimization for automatic voltage regulator system. Transactions of the Institute of Measurement and Control, 41(6), 1761-1771. http,//dx.doi.org/10.1177/0142331218811453. google scholar
  • Li, Y., Ang, K.H. & Chong, G.C.Y. (2006). PID control system analysis and design. IEEE Control Systems Magazine, 26(1),32-41. https,//doi.org/10.1109/ TCST.2005.847331. google scholar Micev, M., Calasan, M., Ali, Z.M., Hasanien, H.M. & Aleem, S.H.E. A. (2021). Optimal design of automatic voltage regulation controller using hybrid simulated annealing - Manta ray foraging optimization algorithm. Ain Shams Engineering Journal, 12, 641-657. https,//doi.org/10.1016/j.asej.2020.07.010. google scholar
  • Mohanty, P.K., Sahu, B.K. & Sidhartha Panda (2014) Tuning and Assessment of Proportional-Integral-Derivative Controller for an Automatic Voltage Regulator System Employing Local Unimodal Sampling Algorithm. Electric Power Components and Systems, 42(9), 959-969. http,//dx.doi.org/10. 1080/15325008.2014.903546 google scholar
  • Panda, S., Sahub, B.K. & Mohanty, P.K. (2012). Design and performance analysis of PID controller for an automatic voltage regulator system using simplified particle swarm optimization. Journal of the Franklin Institute, 349, 2609-2625. http,//dx.doi.org/10.1016/j.jfranklin.2012.06.008 google scholar
  • Sahib, M.A. (2015). A novel optimal PID plus second order derivative controller for AVR system. Engineering Science and Technology an International Journal, 18(2), 194-206. https,//doi.org/10.1016/j.jestch.2014.11.006. google scholar
  • Yousri, D., Hasanien, H.M. & Fathy, A. (2021). Parameters identification of solid oxide fuel cell for static and dynamic simulation using comprehensive learning dynamic multi-swarm marine predators algorithm. Energy Conversion and Management, 228, 113692. https,//doi.org/10.1016/j. enconman.2020.113692. google scholar

Ayrıntılar

Birincil Dil Türkçe
Konular Bilgisayar Bilimleri, Bilgi Sistemleri
Bölüm Araştırma Makalesi
Yazarlar

Zeynep GARİP> (Sorumlu Yazar)
SAKARYA UYGULAMALI BİLİMLER ÜNİVERSİTESİ
0000-0002-0420-8541
Türkiye


Murat Erhan ÇİMEN>
SAKARYA UYGULAMALI BİLİMLER ÜNİVERSİTESİ
0000-0002-1793-485X
Türkiye


Ali Fuat BOZ>
SAKARYA UYGULAMALI BİLİMLER ÜNİVERSİTESİ
0000-0001-6575-7678
Türkiye

Erken Görünüm Tarihi 15 Nisan 2022
Yayımlanma Tarihi 28 Haziran 2022
Yayınlandığı Sayı Yıl 2022, Cilt 6, Sayı 1

Kaynak Göster

Bibtex @araştırma makalesi { acin1026494, journal = {Acta Infologica}, eissn = {2602-3563}, address = {İstanbul Üni. Enformatik Böl. Kalenderhane Mah. 16 Mart Şehitleri Cad. No: 8 Vezneciler Fatih İstanbul}, publisher = {İstanbul Üniversitesi}, year = {2022}, volume = {6}, number = {1}, pages = {53 - 64}, doi = {10.26650/acin.1026494}, title = {Otomatik Gerilim Regülatör Sistemi için Deniz Yırtıcıları Algoritmasının Performans Analizi}, key = {cite}, author = {Garip, Zeynep and Çimen, Murat Erhan and Boz, Ali Fuat} }
APA Garip, Z. , Çimen, M. E. & Boz, A. F. (2022). Otomatik Gerilim Regülatör Sistemi için Deniz Yırtıcıları Algoritmasının Performans Analizi . Acta Infologica , 6 (1) , 53-64 . DOI: 10.26650/acin.1026494
MLA Garip, Z. , Çimen, M. E. , Boz, A. F. "Otomatik Gerilim Regülatör Sistemi için Deniz Yırtıcıları Algoritmasının Performans Analizi" . Acta Infologica 6 (2022 ): 53-64 <https://dergipark.org.tr/tr/pub/acin/issue/69446/1026494>
Chicago Garip, Z. , Çimen, M. E. , Boz, A. F. "Otomatik Gerilim Regülatör Sistemi için Deniz Yırtıcıları Algoritmasının Performans Analizi". Acta Infologica 6 (2022 ): 53-64
RIS TY - JOUR T1 - Otomatik Gerilim Regülatör Sistemi için Deniz Yırtıcıları Algoritmasının Performans Analizi AU - ZeynepGarip, Murat ErhanÇimen, Ali FuatBoz Y1 - 2022 PY - 2022 N1 - doi: 10.26650/acin.1026494 DO - 10.26650/acin.1026494 T2 - Acta Infologica JF - Journal JO - JOR SP - 53 EP - 64 VL - 6 IS - 1 SN - -2602-3563 M3 - doi: 10.26650/acin.1026494 UR - https://doi.org/10.26650/acin.1026494 Y2 - 2022 ER -
EndNote %0 Acta Infologica Otomatik Gerilim Regülatör Sistemi için Deniz Yırtıcıları Algoritmasının Performans Analizi %A Zeynep Garip , Murat Erhan Çimen , Ali Fuat Boz %T Otomatik Gerilim Regülatör Sistemi için Deniz Yırtıcıları Algoritmasının Performans Analizi %D 2022 %J Acta Infologica %P -2602-3563 %V 6 %N 1 %R doi: 10.26650/acin.1026494 %U 10.26650/acin.1026494
ISNAD Garip, Zeynep , Çimen, Murat Erhan , Boz, Ali Fuat . "Otomatik Gerilim Regülatör Sistemi için Deniz Yırtıcıları Algoritmasının Performans Analizi". Acta Infologica 6 / 1 (Haziran 2022): 53-64 . https://doi.org/10.26650/acin.1026494
AMA Garip Z. , Çimen M. E. , Boz A. F. Otomatik Gerilim Regülatör Sistemi için Deniz Yırtıcıları Algoritmasının Performans Analizi. ACIN. 2022; 6(1): 53-64.
Vancouver Garip Z. , Çimen M. E. , Boz A. F. Otomatik Gerilim Regülatör Sistemi için Deniz Yırtıcıları Algoritmasının Performans Analizi. Acta Infologica. 2022; 6(1): 53-64.
IEEE Z. Garip , M. E. Çimen ve A. F. Boz , "Otomatik Gerilim Regülatör Sistemi için Deniz Yırtıcıları Algoritmasının Performans Analizi", Acta Infologica, c. 6, sayı. 1, ss. 53-64, Haz. 2022, doi:10.26650/acin.1026494