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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 4, 2020.
Abstract: In the railway industry, slip control has always been essential due to the low friction and low adhesion between the wheels and the rail and has been an issue for the design, activity, and operation of railroad vehicles. Slip is an unpredictable parameter in the railroad that disintegrates the surface of the railroad with a contact surface of the boggy wheel brought about by the mechanical force of traction phenomena, it destabilizes the railway traction which does not fulfill safety and punctuality requirements. In this paper, we present the work based on developing a fuzzy logic-based anti-slip controller for the commuter train using FPGA implementation which minimizes slip parameters. The development of a fuzzy logic-based anti-slip controller for the commuter train is designed in MATLAB and then tested for area-performance parameters in FPGA through the system generator library. Simulation is performed to demonstrate the effectiveness of the proposed fuzzy logic control system for anti-slip control under various parameters, the results of simulation prove the effectiveness of the proposed control system as compared with conventional PID controller and shows high anti-slip control performance under nonlinearity of brake dynamics.
Fozia Hajano, Tayab D Memon, Farzana Rauf Abro, Imtiaz Hussain Kalwar and Burhan, “Fuzzy Logic based Anti-Slip Control of Commuter Train with FPGA Implementation” International Journal of Advanced Computer Science and Applications(IJACSA), 11(4), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110440
@article{Hajano2020,
title = {Fuzzy Logic based Anti-Slip Control of Commuter Train with FPGA Implementation},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110440},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110440},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {4},
author = {Fozia Hajano and Tayab D Memon and Farzana Rauf Abro and Imtiaz Hussain Kalwar and Burhan}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.