Volume 10, Issue 1 (6-2023)                   IJRARE 2023, 10(1): 1-9 | Back to browse issues page


XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Soltani Nejad M, Mousavi Gazafroudi S M. Parameters Assignment of Electric Train Controller by Using Gravitational Search Optimization Algorithm. IJRARE 2023; 10 (1) :1-9
URL: http://ijrare.iust.ac.ir/article-1-316-en.html
School of Railway Engineering, Iran University of Science and Technology
Abstract:   (593 Views)
The speed profile of the train will be determined according to criteria such as safety, travel convenience, and the type of electric motor used for traction. Due to the passengers and cargo on the train, the electric train load is constantly changing. This will require reassigning the speed controller’s parameters of the electric train. For this purpose, the Gravitational Search optimization Algorithm (GSA) will be used to minimize the error between the setpoint speed profile and the speed profile obtained from the speed controller by using the appropriate assignment of control parameters. This algorithm has a low computational cost and high accuracy, but tuning the adjustable parameters of this algorithm according to the decision space will increase its accuracy. Therefore, by using fuzzy logic Type-I and Type-II, and considering the diversity of population in decision space and generation of population, adjustable parameters of GSA such as 𝐾𝑏𝑒𝑠𝑡 and 𝛼 will be tuned. Finally, a dynamic model of the electric train between two traction power supply substations (TPS) and a proportional-integral-derivative (PID) controller will be simulated in MATLAB software to control the train speed. Then, the controller parameters will be assigned using the GSA algorithm.
Full-Text [PDF 1188 kb]   (308 Downloads)    
Type of Study: Research | Subject: Electrical railway

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | International Journal of Railway Research

Designed & Developed by : Yektaweb