Araştırma Makalesi
Disturbance Rejection Performance Comparison of PSO and ZN Methods for Various Disturbance Frequencies
Öz
In this study Proportional-Integral-Derivative (PID) control of brushed DC Motor is analyzed. The parameters of the PID controller are tuned with two different approaches, namely Ziegler-Nichols (ZN) and Particle Swarm Optimization (PSO). The system is tested under sinusoidal disturbance of varying frequencies in order to evaluate and compare disturbance rejection performances. It is shown that PSO approach has clearly higher performance compared with ZN approach for all disturbance frequencies. Simulations are done using Python programming language with trapezoid rule for differentiation and integration. Results are given in both figures and tables. Comments are done on results and future study is planned.
Anahtar Kelimeler
Kaynakça
- K. Khandani, A. A. Jalali and M. Alipoor, (2009). Particle Swarm Optimization based design of disturbance rejection PID controllers for time delay systems. IEEE International Conference on Intelligent Computing and Intelligent Systems, pp. 862-866, doi: 10.1109/ICICISYS.2009.5358043.
- R. A. Krohling and J. P. Rey, (2001). Design of optimal disturbance rejection PID controllers using genetic algorithms. IEEE Transactions on Evolutionary Computation, 5(1);78-82. doi: 10.1109/4235.910467.
- H.E.A.Ibrahima, F.N.Hassan, Anas O.Shomer. (2014) Optimal PID control of a brushless DC motor using PSO and BF techniques. Ain Shams Engineering Journal, 2(5);391-398.
- Baoye Song, Yihui Xiao and Lin Xu (2020). Design of fuzzy PI controller for brushless DC motor based on PSO–GSA algorithm, Systems Science & Control Engineering, 8(1);67-77. DOI: 10.1080/21642583.2020.1723144.
- Yazgan H, Yener F, Soysal S, Gür A, (2019). Comparison Performances of PSO and GA to Tuning PID Controller for the DC Motor, Sakarya University Journal of Science, 23(2); 162-174.
- Ziegler J G, Nichols N B, 1942, Optimum Settings for Automatic Controllers, Transactions of the American Society of Mechanical Engineers, 64(11);759-765.
- Akyol S, Alataş B, (2012). Current Swarm Intelligence Optimization Algorithms. Nevşehir University Journal of Graduate School of Natural and Applied Sciences, 1(1);36-50.
Yıl 2023,
Cilt: 9 Sayı: 1, 17 - 19, 31.03.2023
Öz
Anahtar Kelimeler
Kaynakça
- K. Khandani, A. A. Jalali and M. Alipoor, (2009). Particle Swarm Optimization based design of disturbance rejection PID controllers for time delay systems. IEEE International Conference on Intelligent Computing and Intelligent Systems, pp. 862-866, doi: 10.1109/ICICISYS.2009.5358043.
- R. A. Krohling and J. P. Rey, (2001). Design of optimal disturbance rejection PID controllers using genetic algorithms. IEEE Transactions on Evolutionary Computation, 5(1);78-82. doi: 10.1109/4235.910467.
- H.E.A.Ibrahima, F.N.Hassan, Anas O.Shomer. (2014) Optimal PID control of a brushless DC motor using PSO and BF techniques. Ain Shams Engineering Journal, 2(5);391-398.
- Baoye Song, Yihui Xiao and Lin Xu (2020). Design of fuzzy PI controller for brushless DC motor based on PSO–GSA algorithm, Systems Science & Control Engineering, 8(1);67-77. DOI: 10.1080/21642583.2020.1723144.
- Yazgan H, Yener F, Soysal S, Gür A, (2019). Comparison Performances of PSO and GA to Tuning PID Controller for the DC Motor, Sakarya University Journal of Science, 23(2); 162-174.
- Ziegler J G, Nichols N B, 1942, Optimum Settings for Automatic Controllers, Transactions of the American Society of Mechanical Engineers, 64(11);759-765.
- Akyol S, Alataş B, (2012). Current Swarm Intelligence Optimization Algorithms. Nevşehir University Journal of Graduate School of Natural and Applied Sciences, 1(1);36-50.
Toplam 7 adet kaynakça vardır.
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Konular | Mühendislik |
| Bölüm | Araştırma Makalesi |
| Yazarlar | |
| Yayımlanma Tarihi | 31 Mart 2023 |
| Gönderilme Tarihi | 10 Kasım 2022 |
| Kabul Tarihi | 17 Ocak 2023 |
| Yayımlandığı Sayı | Yıl 2023 Cilt: 9 Sayı: 1 |
