Türev Filtresi Kullanımının Pathfinder Algoritması ile Optimize Edilmiş Bir PID Denetleyici Üzerindeki Etkisi: Bir DC Motor Hız Kontrol Sistemi Örneği

Year 2024, Volume: 27 Issue: 1, 185 - 196, 29.02.2024

Şeymanur Başlık Erhan Sesli Ömür Akyazı

https://doi.org/10.2339/politeknik.1074261

Abstract

Bu makalede DC motor hız kontrolü için en uygun algoritma ve denetleyici olarak Türev Filtreli Pathfinder Algoritmalı Oransal İntegral Türev denetleyici (TFPFA-OİT) önerilmektedir. Pathfinder algoritması, hayvan kolonisinin ortaklaşa davranışlarından esinlenir ve en iyi beslenme veya av alanını belirlemek için sürülerin liderlik aşama sırasını taklit eder. Tüm parçacıkların hareketi düzenli değildir, hepsi rastgele hareket eder. Pathfinder algoritması ile TFPFA-OİT denetleyicisinin en iyi parametrelerini elde etmek için literatürde sık kullanılan amaç fonksiyonlarından; zaman çarpımı mutlak hatasının integrali (ZÇMHİ) başarım ölçütü kullanılmıştır. Algoritmalar ile denetleyiciler arasında karşılaştırma yapabilmek ve önerilen denetleyicinin yeterliliğini kanıtlamak için MATLAB/Simulink yazılımıyla zaman çözüm kümesi analizi, frekans tepkisi analizi (bode), gürbüzlük analizi, kararlılık analizi ve bozucu yük yanıtı analizleri yapılmıştır. Çalışmalar sonucunda TFPFA-OİT makalede yer alan en iyileştirme algoritmalarından daha iyi başarım elde edildiği görülmüştür.

Keywords

TFPFA-OİT denetleyici, ZÇMHİ, gürbüzlük, DC motor

Effect of Derivative Filter Usage on a PID Controller Optimized via Pathfinder Algorithm: An Example of a DC-MSCS

Abstract

In this article, Pathfinder-Derivative filtered proportional-integral-derivative controller (PF-PIDF) is proposed as the optimum algorithm and controller for DC motor speed control. The Pathfinder algorithm is inspired by the collective behavior of the animal colony and imitates the leadership hierarchy of the herds in order to determine the best meal or hunting ground. The movement of all particles is not regular, they all move randomly. In order to acquire the best parameters of the derivative filtered PID controller (PIDF) controller with the Pathfinder algorithm, the objective function ITAE (Integral of the Time Multiple Absolute Error), one of the commonly used objective functions in the literature, was used. Time solution set analysis, frequency response analysis (bode), robustness analysis, pole-zero map analysis and load disturbance rejection analysis were performed in MATLAB/Simulink software to make comparisons between algorithms and controllers and to testify the sufficiency of the proposed controller. As a result of the studies, it has been seen that the with PIDF Pathfinder algorithm has better performance than the other optimization algorithms in the article.

Keywords

PIDF controller, ITAE, Robustness, DC motor.

References

• [1] 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(2): 331-342, (2021).
• [2] Xue, D., Chen, Y., & Atherton, D. P., “Linear feedback control: analysis and design with MATLAB”, SIAM, Philadelphia-USA, (2007)
• [3] Agarwal, J., Parmar, G., & Gupta, R., “Application of sine cosine algorithm in optimal control of DC motor and robustness analysis”, Wulfenia J, 24(11): 77-95, (2017).
• [4] Bhatt, R., Parmar, G., Gupta, R., & Sikander, A., “Application of stochastic fractal search in approximation and control of LTI systems”, Microsystem Technologies, 25(1): 105-114, (2019).
• [5] Hekimoğlu, 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).
• [6] 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(12): 4997-5006, (2018).
• [7] Khalilpour, M., Razmjooy, N., Hosseini, H., & Moallem, P., “Optimal control of DC motor using invasive weed optimization (IWO) algorithm”, In Majlesi Conference on Electrical Engineering, Majlesi New Town, Isfahan, Iran, (2011).
• [8] Hekimoğlu, B., “Böbrek-ilhamlı algoritma ile ayarlanan PID kontrolör kullanarak DC motor hız kontrolü”, BEU Journal of Science, 8(2): 652-663, (2019).
• [9] Şahin, A. K., Akyazı, Ö., Sahin, E., & Çakır, O., “DC Motorun hız kontrolü için meta-sezgisel algoritma tabanlı PID denetleyici tasarımı”, BEU Journal of Science, 10(2): 533-549, (2021).
• [10] Jaya, A., Purwanto, E., Fauziah, M. B., Murdianto, F. D., Prabowo, G., & Rusli, M. R., “Design of PID-fuzzy for speed control of brushless DC motor in dynamic electric vehicle to improve steady-state performance”, In 2017 International Electronics Symposium on Engineering Technology and Applications (IES-ETA), IEEE, Surabaya, Indonesia, 179-184, (2017).
• [11] Tir, Z., Malik, O., Hamida, M. A., Cherif, H., Bekakra, Y., & Kadrine, A., “Implementation of a fuzzy logic speed controller for a permanent magnet dc motor using a low-cost Arduino platform”, In 2017 5th International Conference on Electrical Engineering-Boumerdes (ICEE-B), IEEE, Boumerdes, Algeria, 1-4, (2017).
• [12] Hamoodi, S. A., Sheet, I. I., & Mohammed, R. A., “A Comparison between PID controller and ANN controller for speed control of DC Motor”, In 2019 2nd International Conference on Electrical, Communication, Computer, Power and Control Engineering (ICECCPCE), IEEE, Mosul, Iraq, 221-224, (2019).
• [13] Rakhonde, S., & Kulkarni, V., “Sliding mode controller (SMC) governed speed control of DC motor”, In 2018 3rd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), Bangalore, India, 1657-1662, (2018).
• [14] Tekerek, A. & Dörterler, M. “The Adaptation of gray wolf optimizer to data clustering”, Journal of Polytechnic, 1-1, (2021). DOI: 10.2339/politeknik.778630
• [15] Ekinci, S. , Hekimoğlu, B. & Uysal, E., “Kidney-inspired algorithm for determination of PID power system stabilizer parameters”, Journal of Polytechnic, 22 (2) : 453-460, (2019).
• [16] Yapici, H., & Cetinkaya, N., “A new meta-heuristic optimizer: Pathfinder algorithm”, Applied Soft Computing, 78: 545-568, (2019).
• [17] Yuan, Z., Li, H., & Yousefi, N., “Optimal hydrogen consumption of fuel cell-based locomotive using speed trajectory optimization by Improved Pathfinder algorithm”, Journal of Cleaner Production, 278: 123430, (2021).
• [18] Priyadarshani, S., Subhashini, K. R., & Satapathy, J. K., “Pathfinder algorithm optimized fractional order tilt-integral-derivative (FOTID) controller for automatic generation control of multi-source power system”, Microsystem Technologies, 27(1): 23-35, (2021).
• [19] Bai, R., & Jermsittiparsert, K., “Optimal design of a micro combined CHP system applying PEM fuel cell as initial mover with utilization of Developed Pathfinder Optimizer”, Energy Reports, 6: 3377-3389, (2020).
• [20] Yapici, H., “Solution of optimal reactive power dispatch problem using pathfinder algorithm”, Engineering Optimization, 53(11): 1946-1963, (2021).
• [21] Qi, X., Yuan, Z., & Song, Y., “A hybrid pathfinder optimizer for unconstrained and constrained optimization problems”, Computational Intelligence and Neuroscience, 2020:1-25, (2020).
• [22] Nguyen, T. T., Nguyen, T. T., Duong, L. T., & Truong, V. A., “An effective method to solve the problem of electric distribution network reconfiguration considering distributed generations for energy loss reduction”, Neural Computing and Applications, 33(5): 1625-1641, (2021).
• [23] Bulut M., “Reference Model Based Adaptive Fuzzy Controller for Direct Current Motor Drive Using Fuzzy Inverse Model”, Journal of Polytechnic, 1-1, (2021)
• [24] Cuoghi, S., & Ntogramatzidis, L., “Inversion formulae for the design of PIDF controllers”, In 2014 4th Australian Control Conference (AUCC), IEEE, Canberra, Australia, 140-145, (2014).
• [25] Şahin, E., & Ayas, M. Ş., “Performance Analysis of Error-Based and User-Defined Objective Functions for a Particle Swarm Optimization Tuned PID Controller with Derivative Filter”, Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, 19(3): 682-689, (2019).
• [26] Şahin, E., “Design of a PID Controller with Fractional Order Derivative Filter for Automatic Voltage Regulation in Power Systems”, 4th International Symposium on Innovative Approaches in Engineering and Natural Sciences (SETSCI), Samsun, Turkey, 4(6): 23-27, (2019).
• [27] Bingül, Z., “Matlab ve Simulink’le Modelleme/Kontrol”, Birsen Yayınevi, İstanbul, Türkiye, (2005).