Doğru Akım Motoru Hız Kontrolü için SAA Tabanlı Kesir Dereceli PI-PD Eklemeli Denetleyici Tasarımı

Year 2024, , 283 - 296, 29.02.2024

Bora Çavdar , Erdinc Sahın , Fatih Nuroglu

https://doi.org/10.2339/politeknik.1139517

Abstract

Bu çalışmada doğru akım (DA) motoru hız kontrolünü sağlamak için eklemeli ve kesir dereceli (FOPI-FOPD) denetleyici tasarımı önerilmiştir. Önerilen denetleyici parametreleri son yıllarda geliştirilen Serçe Arama Algoritması (SAA) ile optimize edilmiştir. Denetleyici parametrelerinin aranması için çeşitli amaç fonksiyonları kullanılmıştır. Bu amaç fonksiyonları zamanla çarpılan mutlak hatanın integrali (ITAE), mutlak hatanın integrali (IAE), zamanla çarpılan hatanın karesinin integrali (ITSE), hatanın karesinin integrali (ISE) ve Zwe-Lee Gaing (ZLG) fonksiyonudur. Zaman bölgesinde aşma (M_p), oturma süresi (t_s) ve yükselme süresi (t_r) bakımından kullanılan amaç fonksiyonlarından elde edilen sonuçlar karşılaştırılmıştır. Ayrıca elde edilen sonuçlar frekans bölgesinde kazanç marjı, faz marjı ve bant genişliği açısından incelenmiştir. Zaman ve frekans bölgesinde farklı amaç fonksiyonlarından elde edilen en iyi sonuç literatürdeki çalışmalarla karşılaştırılmıştır. Ayrıca önerilen denetleyicide elde edilen en iyi sonuç için gürbüzlük, bozucu yük ve referans hız değişimi analizleri incelenmiştir.

Keywords

DA motor hız kontrolü, kesir dereceli denetleyici, SSA, zaman bölgesinde analiz, frekans bölgesinde analiz

SSA-based Fractional Order PI-PD Cascade Controller Design for DC Motor Speed Control

Abstract

In this study, a fractional and cascaded controller type FOPI-FOPD is designed to control the DC motor speed. The proposed controller parameters are tuned via Sparrow Search Algorithm (SSA) which is a recently introduced metaheuristic optimization algorithm. Various types of objective functions are employed to search the proposed controller parameters. These objective functions are the integral of time multiply absolute error (ITAE), the integral of absolute error (IAE),the integral of time multiply squared error (ITSE), the integral of squared error (ISE), and Zwe-Lee Gaing (ZLG). The results obtained from the objective functions were compared in the time domain in terms of overshoot (M_p), settling time (t_s), and ramp time (t_r). In addition, the obtained results are examined in terms of gain margin, phase margin, and bandwidth in the frequency domain. The best results obtained from different objective functions in the time and frequency domain were compared with the studies in the literature. In addition, for the best result obtained in the proposed controller, robustness, disturbance load, and reference speed change analysis were examined.

Keywords

DC motor speed control, fractional order cascade controller, SSA, time domain analysis, frequency domain analysis

References

• [1] Emiroğlu A., Yaren T., Kizir S., “Kendinden ayarlamalı denetleyici ile DA motor hız kontrolü”, Politeknik Dergisi, 25(2): 757-765, (2022).
• [2] Maung, M. M., Latt, M. M., Nwe, C. M., “DC motor angular position control using PID controller with friction compensation”, International journal of scientific and research publications, 8(11): 149-155, (2018).
• [3] Yüksek G., Mete A. N., Alkaya A., “PID parametrelerinin LQR ve GA tabanlı optimizasyonu: sıvı seviye kontrol uygulaması”, Politeknik Dergisi, 23(4): 1111-1119, (2020).
• [4] Şahin H., “Adaptif Hız Kontrol (AHK) Sistemindeki Mesafe Kontrol Sisteminin Sabit Mesafe Ve Sabit Zaman Yöntemleriyle Uygulamalı Olarak Karşılaştırılması”, Politeknik Dergisi, 20(1): 205-210, (2017).
• [5] Sahin, E., “Design of an optimized fractional high order differential feedback controller for load frequency control of a multi-area multi-source power system with nonlinearity”, IEEE Access, 8:12327-12342, (2020).
• [6] Ayas, M. S., “Design of an optimized fractional high-order differential feedback controller for an AVR system” Electrical Engineering, 101(4): 1221-1233, (2019).
• [7] Bitar Z., Sandouk A., al Jabi S., “Testing the Performances of DC Series Motor Used in Electric Car”, Energy Procedia, Elsevier Ltd, 74: 148–159, (2015).
• [8] Li Y., Tong S., Li T., “Adaptive fuzzy output feedback control for a single-link flexible robot manipulator driven DC motor via backstepping”, Nonlinear Analysis: Real World Applications, 14: 483-494 (2013).
• [9] Shah R., Sands T., “Comparing methods of DC motor control for UUVs”, Applied Sciences, 11: (2021).
• [10] Purnama H. S., Sutikno T., Alavandar S.R., Subrata A. C., “Intelligent Control Strategies for Tuning PID of Speed Control of DC Motor-A Review”, IEEE Conference on Energy Conversion (CENCON), 24-30, (2019).
• [11] Rodríguez-Molina A., Villarreal-Cervantes M.G., Aldape-Pérez M., “An adaptive control study for the DC motor using meta-heuristic algorithms”, Soft Computing, 23: 889–906, (2019).
• [12] El-Deen A.T., Hakim Mahmoud A.A., El-Sawi A.R., “Optimal PID tuning for DC motor speed controller based on genetic algorithm”, International Review of Automatic Control, 8: 80–85, (2015).
• [13] Agarwal J., Parmar G., Gupta R., Sikander A., “Analysis of grey wolf optimizer based fractional order PID controller in speed control of DC motor”, Microsystem Technologies, 24: 4997–5006, (2018).
• [14] Agarwal J., Parmar G., Gupta R., “Application of Sine Cosine Algorithm in optimal control of DC motor and robustness analysis”, Wulfenia Journal, 24: 77-95 (2017).
• [15] Ang K.H., Chong G., Li Y., “PID control system analysis, design, and technology”, IEEE Transactions on Control Systems Technology, 13: 559–576, (2005).
• [16] Potnuru D., Alice Mary K., Sai Babu C., “Experimental implementation of Flower Pollination Algorithm for speed controller of a BLDC motor”, Ain Shams Engineering Journal, 10: 287–295, (2019).
• [17] Achanta R.K., Pamula V.K., “DC motor speed control using PID controller tuned by Jaya Optimization Algorithm”, IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI), 983-987, (2017).
• [18] Hekimoglu B., “Optimal tuning of fractional order PID controller for DC motor speed control via Chaotic Atom Search Optimization Algorithm”, IEEE Access, 7: 38100–38114, (2019).
• [19] Şahin A. K., Akyazi Ö., Şahin E., Çakir O., “Dc motorun hız kontrolü için meta-sezgisel algoritma tabanlı PID denetleyici tasarımı”, Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, 10: 533-549 (2021).
• [20] Bhatt R., Parmar G., Gupta R., A. Sikander, “Application of stochastic fractal search in approximation and control of LTI systems”, Microsystem Technologies, 25: 105–114, (2019).
• [21] Ekinci S., Izci D., Hekimoğlu B., “Optimal FOPID speed control of DC motor via Opposition-Based Hybrid Manta Ray Foraging Optimization and simulated Annealing Algorithm”, Arabian Journal for Science and Engineering, 46: 1395–1409, (2021).
• [22] Khanam I., Parmar G., “Application of SFS algorithm in control of DC motor and comparative analysis”, 4th IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics, (UPCON), Institute of Electrical and Electronics Engineers Inc., 256–261, (2017).
• [23] Sahib M.A., Ahmed B.S., “A new multiobjective performance criterion used in PID tuning optimization algorithms”, Journal of Advanced Research, 7: 125–134, (2016).
• [24] Chen Y.Q., Petráš I., Xue D., “Fractional order control - A tutorial”, in: Proceedings of the American Control Conference, 1397–1411, (2009).
• [25] Podlubny I., “Fractional-order systems and PIλDμ-controllers”, IEEE Transactions on Automatic Control, 44: 208–214, (1999).
• [26] Jain R. V., Aware M. V., Junghare A.S., “Tuning of Fractional Order PID controller using particle swarm optimization technique for DC motor speed control”, in: 1st IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES), 1-4, (2017).
• [27] Roy A., Srivastava S., “Design of optimal PIλDδ controller for speed control of DC motor using constrained particle swarm optimization”, in: Proceedings of IEEE International Conference on Circuit, Power and Computing Technologies (ICCPCT), 1-6, (2016).
• [28] Çelik E., Öztürk N., “First application of symbiotic organisms search algorithm to off-line optimization of PI parameters for DSP-based DC motor drives”, Neural Computing and Applications, 30: 1689–1699, (2018).
• [29] Ahmed A., Gupta R., Parmar G., “GWO/PID approach for optimal control of DC motor”, in: 2018 5th International Conference on Signal Processing and Integrated Networks (SPIN), 181–186, (2018).
• [30] Çelik E., Gör H., “Enhanced speed control of a DC servo system using PI + DF controller tuned by stochastic fractal search technique”, J Franklin Inst., 356: 1333–1359, (2019).
• [31] Ekinci S., Hekimoğlu B., Izci D., “Opposition based Henry gas solubility optimization as a novel algorithm for PID control of DC motor”, Engineering Science and Technology, an International Journal, 24: 331–342, (2021).
• [32] Izci D., “Design and application of an optimally tuned PID controller for DC motor speed regulation via a novel hybrid Lévy flight distribution and Nelder–Mead algorithm”, Transactions of the Institute of Measurement and Control, 43: 3195–3211, (2021).
• [33] Çelik E., “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: 1193–1217, (2021).
• [34] Xue J., Shen B., “A novel swarm intelligence optimization approach: sparrow search algorithm”, Systems Science and Control Engineering, 8: 22–34, (2020).
• [35] Nise N.S., “Control Systems Engineering”, John Wiley & Sons, (2020).
• [36] Chapman S. J., “Electric Machinery Fundamentals”, McGraw-Hill, (2004).
• [37] Tabak A., “Maiden application of fractional order PID plus second order derivative controller in automatic voltage regulator”, International Transactions on Electrical Energy Systems, 31: (2021).
• [38] Pan I., Das S., “Fractional order AGC for distributed energy resources using robust optimization”, IEEE Transactions on Smart Grid, 7: 2175–2186, (2016).
• [39] Paliwal N., Srivastava L., Pandit M., “Equilibrium optimizer tuned novel FOPID-DN controller for automatic voltage regulator system”, International Transactions on Electrical Energy Systems, 31: (2021).
• [40] Gaing Z.L., “A particle swarm optimization approach for optimum design of PID controller in AVR system”, IEEE Transactions on Energy Conversion, 19: 384–391, (2004).