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DC motors have a wide range of usage in the industry. So its control is one of the important topics. In literature, there are different control algorithms for the speed control of DC motor. This paper presents a comparative study of PI and Self-Tuning PI controller for the speed control of DC motor. DC motor is modeled and classicPI controller applies for the speed control of DC motor. Pole Placement method is used to get parameters of the PI controller which are Kp and KI. Fuzzy Logic is used for Self-tuning PI controller design. In this controller, Kp and KI controller gains are adjustable parameters and are updated depending on the speed error and change of error. Simulations of these two controllers are performed in the Matlab/Simulink. PI and Self-tuning PI controller are compared and results are given in graphs. The simulation results show that the Self-tuning PI controller has better efficiency than the classic PI controller.

International Conference on Advanced Technologies, Computer Engineering and Science
ICATCES

Nurettin Gökhan Adar Mustafa Eroğlu R. KOZAN

The dynamic behavior of the railway vehicle is an important part of railway transport. Suspension elements affect the dynamic behavior of passenger comfort and railway vehicle components in rail vehicles. In this study, a solid model of 2-degree-of-freedom railway wheels is generated. This model is analyzed with Finite element software. Primary suspension and the ballast elements used in the substructure are used in the finite element model. The primary suspension system reduces the sudden loads from the wagon. On the other hand, the ballast reduces loads by spreading over large areas and absorbing vibrations. In this study, the damping ratio of the primary suspension element is 3 different values (0-39.2-80 Ns/mm) while the ballast spring coefficient is 3 different values (30-65-100 kN/mm) and the ballast damping ratio is 3 different values (0-30-60 Ns/mm). So 27 different analyzes are carried out with the finite element program. As a result of the analysis, the stress of the rail surface, displacement of the rail and the vibration values are determined. A system is formed based on fuzzy logic. Using the fuzzy logic, the dynamic behavior of the railway vehicle for the desired spring and damping values is estimated. The results of the fuzzy logic model and the finite element model are compared, and the fuzzy logic model is accurate up to 90%.

International Symposium on Railway System Engineering
ISERSE

Mustafa Eroğlu Mehmet Akif Koç İsmail Esen Nurettin Gökhan Adar