Research Article
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Design of Hybrid Controller for Automatic Voltage Regulator

Year 2023, Volume: 26 Issue: 1, 199 - 207, 27.03.2023
https://doi.org/10.2339/politeknik.957276

Abstract

Synchronous generators are still the main machines in the production of electrical energy. Changing the excitation current and the rotation speed easily adjust their output voltage and frequency. Since synchronous generators are operated with the grid, the output voltage and frequency must be fixed. Various control systems are used in Automatic Voltage Regulators for adjusting the voltage. In this study, a hybrid controller structure proposed and it operates in MATLAB / Simulink program. The simulation results of the proposed AVR is compared with PID adjusted by Artificial Bee Colonies algorithm and Ziegler-Nichols based different controllers. The comparison was made on maximum overshoot, rise and settling time. According to the comparison made, it was seen that the proposed hybrid controller has better response than the other controllers in terms of maximum overshoot, rise and settling time.

References

  • [1] J Chapman, S. Electric machinery fundamentals. McGraw-hill, (2004).
  • [2] V. Yarlagadda and R. Gnanendar, “Dynamic Stability Improvement Using Genetic Algorithm Tuned Controllers Embeded in Generator Control Loops” 2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC), Erode, India, pp. 561–565, (2020).
  • [3] Ghamri, L. Y., Awadh, H., Al Shamsi, N., AlKhateri, S., Khurram, A., & Rehman, H., "Robust AVR design for the synchronous generator" The Journal of Engineering, 2019(17), 4111-4115, (2019).
  • [4] Farouk, N., & Sheng, L.,. "Design and Implementation of a Fuzzy Logic Controller for Synchronous Generator" Research Journal of Applied Sciences, Engineering and Technology, 4(20), 4126-4131, (2012).
  • [5] Bayram, M. B., Sefa, I., & Balci, S., "A static exciter with interleaved buck converter for synchronous generators" International Journal of Hydrogen Energy, 42(28), 17760-17770, (2017)
  • [6] Elumalai, K., & Sumathi, S. (2017, March). "Behavior modification of PID controller for AVR system using particle swarm optimization" 2017 Conference on Emerging Devices and Smart Systems (ICEDSS), Mallasamudram, India, pp. 190-195, (2017)
  • [7] Ataşlar-Ayyıldız, B., & Karahan, O.. "Controller Tunıng Approach Wıth Tlbo Algorıthm For The Automatıc Voltage Regulator System" Anadolu University of Sciences & Technology-A: Applied Sciences & Engineering, 21(1), (2020).
  • [8] Ercan, K. Ö. S. E., & Coşkun, S., "Time-delay AVR system analysis using PSO-based PID controller", Avrupa Bilim ve Teknoloji Dergisi, (18), 981-991, (2020)..
  • [9] Aboura, F., "Tuning PID controller using hybrid genetic algorithm particle swarm optimization method for AVR system" International Aegean Conference on Electrical Machines and Power Electronics (ACEMP) & 2019 International Conference on Optimization of Electrical and Electronic Equipment (OPTIM), Istanbul, Turkey, pp. 570-574, (2019) .
  • [10] Çelik, E., & Öztürk, N. "A hybrid symbiotic organisms search and simulated annealing technique applied to efficient design of PID controller for automatic voltage regulator" Soft Computing, 22(23), 8011-8024, (2018).
  • [11] Mitra, P., Maulik, S., Chowdhury, S. P., & Chowdhury, S. "ANFIS based automatic voltage regulator with hybrid learning algorithm", 42nd International Universities Power Engineering Conference, Brighton, UK, pp. 397-401 (2007)
  • [12] Mitra, P., Chowdhury, S. P., Chowdhury, S., Pal, S. K., & Crossley, P. A., "Intelligent AVR and PSS with Adaptive hybrid learning algorithm" IEEE Power and Energy Society General Meeting-Conversion and Delivery of Electrical Energy in the 21st Century, Pittsburgh, PA, USA pp. 1-7, (2008)
  • [13] Yegireddy, Narendra Kumar, and Sidhartha Panda. "Design and performance analysis of pid controller for an avr system using multi-objective non-dominated shorting genetic algorithm-ii." 2014 International Conference on Smart Electric Grid (ISEG), Guntur, India, pp. 1-7, 2014.
  • [14] Mohammed, Naeim Farouk, et al. "Tuning of PID controller of synchronous generators using genetic algorithm" 2014 IEEE International Conference on Mechatronics and Automation, Tianjin, China, pp. 1544-1548, (2014).
  • [15] Al Gizi, A. J., Mustafa, M. W., Al-geelani, N. A., & Alsaedi, M. A., "Sugeno fuzzy PID tuning, by genetic-neutral for AVR in electrical power generation" Applied Soft Computing, 28: 226-236. (2015).
  • [16] Gaing, Z. L., "A particle swarm optimization approach for optimum design of PID controller in AVR system" IEEE Tansactions on Energy Conversion, 19(2), 384-391, (2004)
  • [17] Farouk, N., & Bingqi, T. "Application of self-tuning fuzzy PID controller on the AVR system" IEEE International Conference on Mechatronics and Automation, Chengdu, China, pp. 2510-2514, (2012).
  • [18] Odu, G. O. "Weighting methods for multi-criteria decision making technique" Journal of Applied Sciences and Environmental Management, 23(8), 1449-1457, (2019).
  • [19] Li, Wu, Yonggang Chen, and Yang Chen. "Generalizing TOPSIS for multi-criteria group decision-making with weighted ordinal preferences." 7th World Congress on Intelligent Control and Automation, Chongqing, China, pp. 7505-7508, (2008).
  • [20] Özçalıcı, M. "Matlab ile çok kriterli karar verme teknikleri" Nobel Akademik Yayıncılık, Ankara, (2017).
  • [21] Özdemir, M. "TOPSIS", Operasyonel Yönetsel ve Stratejik Problemlerin Çözümünde Çok Kriterli Karar Verme Yöntemleri, Dora Yayınevi, İstanbul, (2014)
  • [22] Özdemir, M. T., & Çelik, V. "Stability analysis of the automatic voltage regulation system with PI controller" Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 21(4), 698-705, (2017).
  • [23] Ekinci, S., Demiroren, A., Zeynelgil, H., & Hekimoğlu, B., "An opposition-based atom search optimization algorithm for automatic voltage regulator system" J. Fac. Eng. Archit. Gazi Univ., 35, 1141-1158, (2020).
  • [24] Bayram, M. Baha, et al. "Matlab/GUI based basic design principles of PID controller in AVR." 4th International Conference on Power Engineering, Energy and Electrical Drives. Istanbul, Turkey, pp. 1017-1022, (2013).
  • [25] Devaraj, D., & Selvabala, B., "Real-coded genetic algorithm and fuzzy logic approach for real-time tuning of proportional–integral–derivative controller in automatic voltage regulator system" IET Generation, Transmission & Distribution, 3(7), 641-649, (2009).
  • [26] Eke, İ., Taplamacıoğlu, M. C., & Kocaarslan, İ., "Yapay Ari Kolonisi Algoritmasi Tabanli Kararli Güç Sistemi Dengeleyicisi Tasarımı" Journal of the Faculty of Engineering & Architecture of Gazi University, 26(3), (2011).
  • [27] B. Özgenç, M. Ş. Ayas, and İ. H. Altaş, “Optimally Tuned PID Controller Design for an AVR System: A Comparison Study,” Int. J. Multidiscip. Stud. Innov. Technol., 3(2), pp. 157–161, (2019).
  • [28] Ang, K. H., & Chong, G. Yun li., "PID control system analysis, design, and technology" IEEE Transaction on Control Systems Technology, 13(4), 559-576, (2005).
  • [29] Köse, E., "Optimal Control of AVR System With Tree Seed Algorithm-Based PID Controller" IEEE Access, 8, 89457-89467, (2020).
  • [30] Chao, C. T., Sutarna, N., Chiou, J. S., & Wang, C. J., "An optimal fuzzy PID controller design based on conventional PID control and nonlinear factors" Applied Sciences, 9(6), 1224, (2019).
  • [31] McCormack, A. S., & Godfrey, K. R. "Rule-based autotuning based on frequency domain identification" IEEE Transactions on Control Systems Technology, 6(1), 43-61, (1998).
  • [32] Tzafestas, S., & Papanikolopoulos, N. P., "Incremental fuzzy expert PID control" IEEE Transactions on Industrial Electronics, 37(5), 365-371, (1990).
  • [33] Elmas, Ç., "Yapay Zeka Uygulamaları", Seçkin Yayıncılık, (2018).
  • [34] Gupta, Tripti, and D. K. Sambariya. "Optimal design of fuzzy logic controller for automatic voltage regulator." 2017 International Conference on İnformation, Communication, Instrumentation and Control (ICICIC), Indore, India, pp. 1-6, (2017).
  • [35] Torun, Y., Ergül, Z., & Aksöz, "A. Optimum Enerji Verimliliğini Hedefleyen Rastgele Ağaçlar ve Yapay Arı Kolonisi Yöntemi ile Otonom Robotlarda Yol Planlama Algoritması" Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji, 7(4), 903-915, (2019).
  • [36] Öztürk, S. & Öztürk, N., "Yapay Arı Koloni Algoritması Kullanılarak Görüntü İyileştirme Yönteminin Geliştirilmesi" Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji, 4 (4) , 173-183, (2016).
  • [37] Karaboga, D., and Gorkemli, B., "A combinatorial artificial bee colony algorithm for traveling salesman problem." 2011 International Symposium on Innovations in Intelligent Systems and Applications, Istanbul, Turkey, pp. 50-53, (2011).
  • [38] Karaboga, D., & Akay, B., "A comparative study of artificial bee colony algorithm" Applied Mathematics And Computation, 214(1), 108-132. (2009).

Otomatik Gerilim Regülatörü İçin Hibrit Bir Denetleyici Tasarımı

Year 2023, Volume: 26 Issue: 1, 199 - 207, 27.03.2023
https://doi.org/10.2339/politeknik.957276

Abstract

Senkron generatörler elektrik enerjisinin üretiminde temel makina olma görevini sürdürmektedir. Senkron generatörlerin çıkış gerilimi ve frekansı uyartım akımı ve devir sayısı değiştirilerek kolayca ayarlanabilmektedir. Genellikle senkron generatörler şebekeye bağlı olarak çalıştıkları için çıkış gerilimi ve frekansının sabit olması gerekmektedir. Gerilimin ayarlanması için kullanılan Otomatik Gerilim Regülatörlerinde çeşitli denetleyici sistemler kullanılmaktadır. Bu çalışmada MATLAB/Simulink programında bulanık mantık tabanlı anahtarlamalı bir hibrit denetleyici yapısı önerilmiştir. Önerilen hibrit denetleyici, Yapay Arı Kolonisi Algoritması kullanılarak optimize edilen PID denetleyiciyle ve Ziegler-Nichols yöntemine dayalı farklı denetleyicilerden elde edilen sonuçlarla karşılaştırılmıştır. Karşılaştırma kriterleri maksimum aşım miktarı, yükselme zamanı ve oturma zamanı olarak belirlenmiştir. Karşılaştırmanın sonuçları da çok kriterli karar verme tekniklerinden biri olan TOPSIS metodu ile analiz edilerek değerlendirilmiş ve sunulmuştur.

References

  • [1] J Chapman, S. Electric machinery fundamentals. McGraw-hill, (2004).
  • [2] V. Yarlagadda and R. Gnanendar, “Dynamic Stability Improvement Using Genetic Algorithm Tuned Controllers Embeded in Generator Control Loops” 2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC), Erode, India, pp. 561–565, (2020).
  • [3] Ghamri, L. Y., Awadh, H., Al Shamsi, N., AlKhateri, S., Khurram, A., & Rehman, H., "Robust AVR design for the synchronous generator" The Journal of Engineering, 2019(17), 4111-4115, (2019).
  • [4] Farouk, N., & Sheng, L.,. "Design and Implementation of a Fuzzy Logic Controller for Synchronous Generator" Research Journal of Applied Sciences, Engineering and Technology, 4(20), 4126-4131, (2012).
  • [5] Bayram, M. B., Sefa, I., & Balci, S., "A static exciter with interleaved buck converter for synchronous generators" International Journal of Hydrogen Energy, 42(28), 17760-17770, (2017)
  • [6] Elumalai, K., & Sumathi, S. (2017, March). "Behavior modification of PID controller for AVR system using particle swarm optimization" 2017 Conference on Emerging Devices and Smart Systems (ICEDSS), Mallasamudram, India, pp. 190-195, (2017)
  • [7] Ataşlar-Ayyıldız, B., & Karahan, O.. "Controller Tunıng Approach Wıth Tlbo Algorıthm For The Automatıc Voltage Regulator System" Anadolu University of Sciences & Technology-A: Applied Sciences & Engineering, 21(1), (2020).
  • [8] Ercan, K. Ö. S. E., & Coşkun, S., "Time-delay AVR system analysis using PSO-based PID controller", Avrupa Bilim ve Teknoloji Dergisi, (18), 981-991, (2020)..
  • [9] Aboura, F., "Tuning PID controller using hybrid genetic algorithm particle swarm optimization method for AVR system" International Aegean Conference on Electrical Machines and Power Electronics (ACEMP) & 2019 International Conference on Optimization of Electrical and Electronic Equipment (OPTIM), Istanbul, Turkey, pp. 570-574, (2019) .
  • [10] Çelik, E., & Öztürk, N. "A hybrid symbiotic organisms search and simulated annealing technique applied to efficient design of PID controller for automatic voltage regulator" Soft Computing, 22(23), 8011-8024, (2018).
  • [11] Mitra, P., Maulik, S., Chowdhury, S. P., & Chowdhury, S. "ANFIS based automatic voltage regulator with hybrid learning algorithm", 42nd International Universities Power Engineering Conference, Brighton, UK, pp. 397-401 (2007)
  • [12] Mitra, P., Chowdhury, S. P., Chowdhury, S., Pal, S. K., & Crossley, P. A., "Intelligent AVR and PSS with Adaptive hybrid learning algorithm" IEEE Power and Energy Society General Meeting-Conversion and Delivery of Electrical Energy in the 21st Century, Pittsburgh, PA, USA pp. 1-7, (2008)
  • [13] Yegireddy, Narendra Kumar, and Sidhartha Panda. "Design and performance analysis of pid controller for an avr system using multi-objective non-dominated shorting genetic algorithm-ii." 2014 International Conference on Smart Electric Grid (ISEG), Guntur, India, pp. 1-7, 2014.
  • [14] Mohammed, Naeim Farouk, et al. "Tuning of PID controller of synchronous generators using genetic algorithm" 2014 IEEE International Conference on Mechatronics and Automation, Tianjin, China, pp. 1544-1548, (2014).
  • [15] Al Gizi, A. J., Mustafa, M. W., Al-geelani, N. A., & Alsaedi, M. A., "Sugeno fuzzy PID tuning, by genetic-neutral for AVR in electrical power generation" Applied Soft Computing, 28: 226-236. (2015).
  • [16] Gaing, Z. L., "A particle swarm optimization approach for optimum design of PID controller in AVR system" IEEE Tansactions on Energy Conversion, 19(2), 384-391, (2004)
  • [17] Farouk, N., & Bingqi, T. "Application of self-tuning fuzzy PID controller on the AVR system" IEEE International Conference on Mechatronics and Automation, Chengdu, China, pp. 2510-2514, (2012).
  • [18] Odu, G. O. "Weighting methods for multi-criteria decision making technique" Journal of Applied Sciences and Environmental Management, 23(8), 1449-1457, (2019).
  • [19] Li, Wu, Yonggang Chen, and Yang Chen. "Generalizing TOPSIS for multi-criteria group decision-making with weighted ordinal preferences." 7th World Congress on Intelligent Control and Automation, Chongqing, China, pp. 7505-7508, (2008).
  • [20] Özçalıcı, M. "Matlab ile çok kriterli karar verme teknikleri" Nobel Akademik Yayıncılık, Ankara, (2017).
  • [21] Özdemir, M. "TOPSIS", Operasyonel Yönetsel ve Stratejik Problemlerin Çözümünde Çok Kriterli Karar Verme Yöntemleri, Dora Yayınevi, İstanbul, (2014)
  • [22] Özdemir, M. T., & Çelik, V. "Stability analysis of the automatic voltage regulation system with PI controller" Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 21(4), 698-705, (2017).
  • [23] Ekinci, S., Demiroren, A., Zeynelgil, H., & Hekimoğlu, B., "An opposition-based atom search optimization algorithm for automatic voltage regulator system" J. Fac. Eng. Archit. Gazi Univ., 35, 1141-1158, (2020).
  • [24] Bayram, M. Baha, et al. "Matlab/GUI based basic design principles of PID controller in AVR." 4th International Conference on Power Engineering, Energy and Electrical Drives. Istanbul, Turkey, pp. 1017-1022, (2013).
  • [25] Devaraj, D., & Selvabala, B., "Real-coded genetic algorithm and fuzzy logic approach for real-time tuning of proportional–integral–derivative controller in automatic voltage regulator system" IET Generation, Transmission & Distribution, 3(7), 641-649, (2009).
  • [26] Eke, İ., Taplamacıoğlu, M. C., & Kocaarslan, İ., "Yapay Ari Kolonisi Algoritmasi Tabanli Kararli Güç Sistemi Dengeleyicisi Tasarımı" Journal of the Faculty of Engineering & Architecture of Gazi University, 26(3), (2011).
  • [27] B. Özgenç, M. Ş. Ayas, and İ. H. Altaş, “Optimally Tuned PID Controller Design for an AVR System: A Comparison Study,” Int. J. Multidiscip. Stud. Innov. Technol., 3(2), pp. 157–161, (2019).
  • [28] Ang, K. H., & Chong, G. Yun li., "PID control system analysis, design, and technology" IEEE Transaction on Control Systems Technology, 13(4), 559-576, (2005).
  • [29] Köse, E., "Optimal Control of AVR System With Tree Seed Algorithm-Based PID Controller" IEEE Access, 8, 89457-89467, (2020).
  • [30] Chao, C. T., Sutarna, N., Chiou, J. S., & Wang, C. J., "An optimal fuzzy PID controller design based on conventional PID control and nonlinear factors" Applied Sciences, 9(6), 1224, (2019).
  • [31] McCormack, A. S., & Godfrey, K. R. "Rule-based autotuning based on frequency domain identification" IEEE Transactions on Control Systems Technology, 6(1), 43-61, (1998).
  • [32] Tzafestas, S., & Papanikolopoulos, N. P., "Incremental fuzzy expert PID control" IEEE Transactions on Industrial Electronics, 37(5), 365-371, (1990).
  • [33] Elmas, Ç., "Yapay Zeka Uygulamaları", Seçkin Yayıncılık, (2018).
  • [34] Gupta, Tripti, and D. K. Sambariya. "Optimal design of fuzzy logic controller for automatic voltage regulator." 2017 International Conference on İnformation, Communication, Instrumentation and Control (ICICIC), Indore, India, pp. 1-6, (2017).
  • [35] Torun, Y., Ergül, Z., & Aksöz, "A. Optimum Enerji Verimliliğini Hedefleyen Rastgele Ağaçlar ve Yapay Arı Kolonisi Yöntemi ile Otonom Robotlarda Yol Planlama Algoritması" Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji, 7(4), 903-915, (2019).
  • [36] Öztürk, S. & Öztürk, N., "Yapay Arı Koloni Algoritması Kullanılarak Görüntü İyileştirme Yönteminin Geliştirilmesi" Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji, 4 (4) , 173-183, (2016).
  • [37] Karaboga, D., and Gorkemli, B., "A combinatorial artificial bee colony algorithm for traveling salesman problem." 2011 International Symposium on Innovations in Intelligent Systems and Applications, Istanbul, Turkey, pp. 50-53, (2011).
  • [38] Karaboga, D., & Akay, B., "A comparative study of artificial bee colony algorithm" Applied Mathematics And Computation, 214(1), 108-132. (2009).
There are 38 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Research Article
Authors

Güngör Bal 0000-0002-0564-5903

Nihat Ozturk 0000-0002-0607-1868

Selim Öncü 0000-0001-6432-0634

Kenan Ünal 0000-0002-2660-8386

Publication Date March 27, 2023
Submission Date June 24, 2021
Published in Issue Year 2023 Volume: 26 Issue: 1

Cite

APA Bal, G., Ozturk, N., Öncü, S., Ünal, K. (2023). Otomatik Gerilim Regülatörü İçin Hibrit Bir Denetleyici Tasarımı. Politeknik Dergisi, 26(1), 199-207. https://doi.org/10.2339/politeknik.957276
AMA Bal G, Ozturk N, Öncü S, Ünal K. Otomatik Gerilim Regülatörü İçin Hibrit Bir Denetleyici Tasarımı. Politeknik Dergisi. March 2023;26(1):199-207. doi:10.2339/politeknik.957276
Chicago Bal, Güngör, Nihat Ozturk, Selim Öncü, and Kenan Ünal. “Otomatik Gerilim Regülatörü İçin Hibrit Bir Denetleyici Tasarımı”. Politeknik Dergisi 26, no. 1 (March 2023): 199-207. https://doi.org/10.2339/politeknik.957276.
EndNote Bal G, Ozturk N, Öncü S, Ünal K (March 1, 2023) Otomatik Gerilim Regülatörü İçin Hibrit Bir Denetleyici Tasarımı. Politeknik Dergisi 26 1 199–207.
IEEE G. Bal, N. Ozturk, S. Öncü, and K. Ünal, “Otomatik Gerilim Regülatörü İçin Hibrit Bir Denetleyici Tasarımı”, Politeknik Dergisi, vol. 26, no. 1, pp. 199–207, 2023, doi: 10.2339/politeknik.957276.
ISNAD Bal, Güngör et al. “Otomatik Gerilim Regülatörü İçin Hibrit Bir Denetleyici Tasarımı”. Politeknik Dergisi 26/1 (March 2023), 199-207. https://doi.org/10.2339/politeknik.957276.
JAMA Bal G, Ozturk N, Öncü S, Ünal K. Otomatik Gerilim Regülatörü İçin Hibrit Bir Denetleyici Tasarımı. Politeknik Dergisi. 2023;26:199–207.
MLA Bal, Güngör et al. “Otomatik Gerilim Regülatörü İçin Hibrit Bir Denetleyici Tasarımı”. Politeknik Dergisi, vol. 26, no. 1, 2023, pp. 199-07, doi:10.2339/politeknik.957276.
Vancouver Bal G, Ozturk N, Öncü S, Ünal K. Otomatik Gerilim Regülatörü İçin Hibrit Bir Denetleyici Tasarımı. Politeknik Dergisi. 2023;26(1):199-207.