Design and Control of EMS Magnetic Levitation Train using Fuzzy MRAS and PID Controllers

International Journal of Advance Research and Innovative Ideas in Education 6 (2):1023-1031 (2020)
  Copy   BIBTEX

Abstract

In this paper, a Magnetic Levitation (MAGLEV) train is designed with a first degree of freedom electromagnetbased totally system that permits to levitate vertically up and down. Fuzzy logic, PID and MRAS controllers are used to improve the Magnetic Levitation train passenger comfort and road handling. A Matlab Simulink model is used to compare the performance of the three controllers using step input signals. The stability of the Magnetic Levitation train is analyzed using root locus technique. Controller output response for different time period and change of air gap with different time period is analyzed for the three controllers. Finally the comparative simulation and experimental results demonstrate the effectiveness of the presented fuzzy logic controller.

Links

PhilArchive

External links

  • This entry has no external links. Add one.
Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

Truth transformation fuzzy logic controllers: Outlines of the design of a new generation of fuzzy controllers.L. H. Sultan & T. H. Janabi - 1991 - Ai 1991 Frontiers in Innovative Computing for the Nuclear Industry Topical Meeting, Jackson Lake, Wy, Sept. 15-18, 1991 1.
Fuzzy control approaches, General design schemes, Structure of a fuzzy controller.R. Palm - 1998 - In Enrique H. Ruspini, Piero Patrone Bonissone & Witold Pedrycz (eds.), Handbook of Fuzzy Computation. Institute of Physics.
Comparison of PID and MPC controllers for continuous stirred tank reactor (CSTR) concentration control.Mustefa Jibril, Mesay Tadesse & Elias Alemayehu - 2020 - International Research Journal of Modernization in Engineering Technology and Science 2 (4):133-140.
Comparison of DC motor speed control performance using fuzzy logic and model predictive control method.Mustefa Jibril - 2020 - International Research Journal of Modernization in Engineering Technology and Science 2 (4):141-145.
DC motor speed control with the presence of input disturbance using neural network based model reference and predictive controllers.Mustefa Jibril - 2020 - International Research Journal of Modernization in Engineering Technology and Science 2 (4):103-110.
Fuzzy control approaches, Sliding mode fuzzy control.R. Palm - 1998 - In Enrique H. Ruspini, Piero Patrone Bonissone & Witold Pedrycz (eds.), Handbook of Fuzzy Computation. Institute of Physics.

Analytics

Added to PP
2020-04-23

Downloads
913 (#15,399)

6 months
253 (#9,555)

Historical graph of downloads
How can I increase my downloads?

Author's Profile

Mustefa Jibril
Dire Dawa University

Citations of this work

No citations found.

Add more citations

References found in this work

No references found.

Add more references