@article{MAKHILLIJEPE202115225339,
    title = {Stability Control of EMS Maglev Train using New Lambda (λ) Tuning Approach of Single
Input Fuzzy Logic using Gradient Descent Algorithm and Particle Swarm Optimization},
    journal = {International Journal of Electrical and Power Engineering},
    volume = {15},
    number = {2},
    pages = {17-23},
    year = {2021},
    issn = {1990-7958},
    doi = {ijepe.2021.17.23},
    url = {https://makhillpublications.co/view-article.php?issn=1990-7958&doi=ijepe.2021.17.23},
    author = {Mustefa,Mesay and},
    keywords = {Magnetically levitated train,single input fuzzy logic control,gradient descent algorithm,particle swarm optimization,proportional integral derivative},
    abstract = {Magnetically Levitated (Maglev) trains to
change from traditional trains in that they are regenerated,
oriented and driven along a guided path using a variable
magnetic field. This study introduces a new approach to
the development of SIFLC and GDA and PSO for the
implementation of EMS Maglev Train displacement
control. The Maglev train was modeled using the
mathematical modeling technique to mimic the
displacement control system. The PID controller is
modeled as the default controller. SIFLC was then
modeled in three heuristic tuning methods. The real-time
system model has been simulated using MATLAB and
rise time (Tr), percentage overshoot (OS) and settling
time (Ts) for the Maglev displacement and stability
control have been compared and analyzed. The result
shows that the SIFLC GDA output has an excellent effect
on the specifications of 0.1021% (OS), 2.1332s (Tr) and
17.9790s (Ts).}
    }