Genetic algorithm-PID controller for model order reduction pantographcatenary system

• Autorzy: Al-Awad Nasir A. , Abboud Izz K. , Al-Rawi Muaayed F.

Identyfikatory

DOI

10.23743/acs-2021-11

• Języki publikacji: EN

Abstrakty

EN

Controlling the contact force between the pantograph and the catenary has come to be a requirement for improving the performances and affectivity of high-speed train systems Indeed, these performances can also significantly be decreased due to the fact of the catenary equal stiffness variation. In addition, the contact force can also additionally differ and ought to end up null, which may additionally purpose the loss of contact. Then, in this paper, we current an active manipulate of the minimize order model of pantograph-catenary system. The proposed manipulate approach implements an optimization technique, like particle swarm (PSO), the usage of a frequent approximation of the catenary equal stiffness. All the synthesis steps of the manipulate law are given and a formal evaluation of the closed loop stability indicates an asymptotic monitoring of a nominal steady contact force. Then, the usage of Genetic Algorithm with Proportional-Integral-derivative (G.A-PID) as proposed controller appeared optimum response where, the contacts force consequences to be virtually equal to its steady reference. Finally it seems the advantageous of suggestion approach in contrast with classical manipulate strategies like, Internal mode control(IMC) method, linear quadratic regulator (LQR). The outcomes via the use of MATLAB simulation, suggests (G.A-PID) offers better transient specifications in contrast with classical manipulate.

Słowa kluczowe

EN

pantograph system; model reduction; PSO; G.A-PID; IMC; LQR

PL

system pantografowy; redukcja modelu; PSO; G.A-PID; IMC; LQR

• Wydawca: Polskie Towarzystwo Promocji Wiedzy ; Lublin University of Technology
• Czasopismo: Applied Computer Science
• Rocznik: 2021
• Tom: Vol. 17, no 2
• Strony: 28--39
• Opis fizyczny: Bibliogr. 16 poz., fig., tab.

Twórcy

autor

Al-Awad Nasir A.

• Mustansiriyah University, Faculty of Engineering, Computer Engineering Department, Baghdad, Iraq

• https://orcid.org/0000-0000-0003-5030

autor

Abboud Izz K.

• Mustansiriyah University, Faculty of Engineering, Computer Engineering Department, Baghdad, Iraq

• https://orcid.org/0000-0002-8344-8585

autor

Al-Rawi Muaayed F.

• Mustansiriyah University, Faculty of Engineering, Computer Engineering Department, Baghdad, Iraq

• https://orcid.org/0000-0003-1841-1222

Bibliografia

• [1] Al-Awad, N., & Al-Seady, A. (2020). Fuzzy Controller of Model Reduction Distillation Column with Minimal Rules. Applied Computer Science, 16(2), 80–94. https://doi.org/10.23743/acs-2020-14
• [2] Arnold, M., & Simenon, B. (2000). Pantograph and catenary dynamics: a benchmark problem and its numerical solution. Applied Numerical Mathematics, 34(4), 345–362. https://doi.org/10.1016/S0168-9274(99)00038-0
• [3] Bartolini, G., Pisano, A., Punta, E., & Usai, E. (2003). A survey of applications of second-order sliding mode control to mechanical systems. International Journal of Control, 76(9–10), 875–892. https://doi.org/10.1080/0020717031000099010
• [4] Chater, E., Ghani, D., Giri, F., & Haloua, M. (2015). Output feedback control of pantograph–catenary system with adaptive estimation of catenary parameters. Journal of Modern Transportation, 23, 252–261. https://doi.org/10.1007/s40534-015-0085-z
• [5] Giovanelli, D., & Farella, E. (2016). Force Sensing Resistor and Evaluation of Technology for Wearable Body Pressure Sensing. Journal of Sensors, 3, 9391850. https://doi.org/10.1155/2016/9391850
• [6] Haamed, R., & Hameed, E. (2020). Controlling the Mean Arterial Pressure by Modified Model Reference Adaptive Controller Based on Two Optimization Algorithms. Applied Computer Science, 16(2), 53–67. https://doi.org/10.23743/acs-2020-12
• [7] Kennedy, J., & Eberhart, R. (2016). Particle swarm optimization. In IEEE International Conference on Neural Networks, (vol. 4, pp. 1942–1948). IEEE. https://doi.org/10.1109/ICNN.1995.488968
• [8] Kłosowski, G., Klepka, T., & Nowacka, A. (2018). Neural Controller for the Selection of Recycled Components in Polymer-Gypsy Mortars. Applied Computer Science, 14(2), 48–59. https://doi.org/10.23743/acs-2018-12
• [9] Lin, Y., Lin, C., & Yang, C. (2007). Robust active vibration control for rail vehicle pantograph. IEEE transactions on vehicular technology, 56(4), 1994–2004. https://doi.org/10.1109/TVT.2007.897246
• [10] Liu, R., Qian, C., Liu, S., & Jin, Y.-F. (2016). State feedback control design for Boolean networks. BMC Systems Biology, 10, 70. https://doi.org/10.1186/s12918-016-0314-z
• [11] Makino, T., Yoshida, K., Seto, S., & Makino, K. (2018). Running test on current collector with contact force controller for high-speed railway. JSME International Journal Series C, 40(4), 671–680. https://doi.org/10.1299/jsmec.40.671
• [12] Matvejevs, An., & Matvejevs, Al. (2011). Optimal Control of Pantograph-Catenary System Based on Parametric Identification. Scientific Journal of Riga Technical University Computer Science. Information Technology and Management Science, 49.
• [13] O’Connor, D., Eppinger, S., Seering, W., & Wormley, D. (1997). Active control of a high-speed pantograph. Journal of Dynamic Systems, Measurement and Control, 119(1), 1–4. https://doi.org/10.1115/1.2801209
• [14] Pisano, A., & Usai, E. (2008). Contact force regulation in wire-actuated pantographs via variable structure control and frequency-domain techniques. International Journal of Control, 81(11), 1747–1762. https://doi.org/10.1080/00207170701874473
• [15] Pourzeynali, S., Lavasani, H.H., & Modarayi, A.H. (2007). Active control of high rise building structures using fuzzy logic and genetic Algorithms. Engineering Structures, 29(3), 346–357. https://doi.org/10.1016/j.engstruct.2006.04.015
• [16] Shudong, W., Jingbo, G., & Guosheng, G. (2008). Research of the active control for high-speed train pantograph. In IEEE International Conference on Cybernetics and Intelligent Systems (pp. 749–753). IEEE. https://doi.org/10.1109/ICCIS.2008.4670754

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).