Yazar "Bakir, Hincal Gokhan" seçeneğine göre listele

Listeleniyor 1 - 3 / 3
  • Küçük Resim Yok
    Öğe
    Control method simulation and application for autonomous vehicles
    (Ieee, 2018) Arikan, Abdullah; Kayaduman, Abdulsamed; Polat, Suat; Simsek, Yasin; Dikmen, Ismail Can; Bakir, Hincal Gokhan; Karadag, Teoman
    Autonomous vehicles can be operated without the need for human intervention by perceiving their physical environment, thanks to their automatic control systems. At present, extensive studies on autonomous land, sea, and air vehicles are ongoing all around the world. This project is focused on autonomous land vehicles. In the simplest examples, the speed and position of the vehicle can be controlled with the position sensor in the front wheel section and the speed sensors in the rear wheel section. Autonomy is achieved by generating signals for the control system by interpreting the data from various sensors on the vehicle with the aid of an algorithm. Different control methods can be applied for such vehicles. Within the scope of this project, the control of the vehicle will be provided by PID (Proportional-Integral-Derivative) control method, in order to constitute a basis for autonomous vehicle technology,
  • Küçük Resim Yok
    Öğe
    Development and application of sensor network for autonomous vehicles
    (Ieee, 2018) Kayaduman, Abdulsamed; Arikan, Abdullah; Dikmen, Ismail Can; Bakir, Hincal Gokhan; Karadag, Teoman; Abbasov, Teymuraz
    Autonomous vehicles are self-driving vehicles by interpreting data gathered from the environment through sensors. A set of sensors on the vehicle collects the raw data from the environment in which the vehicle is interacting. The software algorithms interpret the data from the sensors and generate commands for the vehicle to follow the path, change direction and maneuver. In this project, the data from the camera module and various sensors were processed and interpreted by means of software libraries on a network composed of micro controllers. Camera modules and image processing algorithms are used to detect strips along the roadside. The resulting images and the data from the other sensors generate the necessary commands for the vehicle's movement with a pivotal software formed on the embedded system. By this means the model autonomous vehicle gain self-motion capability by perceiving its surroundings.
  • Küçük Resim Yok
    Öğe
    Modeling of particle-capture mechanism of axial magnetic filter in bounded flow field with variable viscosity
    (Taylor & Francis Inc, 2020) Karadag, Teoman; Bakir, Hincal Gokhan
    The capture mechanism of micron-sized magnetic particles from a surfactant-containing suspension is examined in an axial magnetic filter with a bounded flow field by using the particle trajectory model. The effects of change in the suspension viscosity to the suspension flow velocity are modeled. Analytical and numerical solutions for the particle trajectory model are obtained for a laminar flow regime. It is evaluated that the magnetic particles in the suspension, subjected to a viscosity change, are captured in a gradient magnetic field formed by a magnetized external ferromagnetic wire and the capturing of particles gets harder due to condensation of surfactant layers.