Design and Control of a Magnetic-Wheeled Climbing Robot for Vertical Steel Surfaces: Motor Positioning Performance Through Model Reference Adaptive Control


Yaşar C. F., Tacal Ucun B., Ucun L.

2024 25th International Carpathian Control Conference (ICCC), Krakow, Polonya, 22 - 24 Mayıs 2024, ss.1-6

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/iccc62069.2024.10569287
  • Basıldığı Şehir: Krakow
  • Basıldığı Ülke: Polonya
  • Sayfa Sayıları: ss.1-6
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

Climbing robots capable of performing activities on vertical steel walls are frequently utilized in the maintenance of high-rise structures and unsafe situations for human workers, including bridges, ships, liquid tanks, chimneys, pipelines, nuclear facilities, and wind turbines. A climbing robot outfitted with the necessary equipment performs activities such as monitoring, cleaning, search and rescue, and more. The fundamental aim is to design a sturdy and safe robotic system with an adhesion-to-the-wall approach that can move on the surface while carrying the essential sensing system, actuation, and drive system as power cables or suppliers. The principal restrictions are the large forces that appear in the system and directly affect the motors. This paper presents a climbing robot design with magnetic wheels powered by a direct current motor; a simplified model with experimental parameter identification is utilized, and a model incorporating all forces is used to develop and test a model reference adaptive controller. Coulomb friction, magnetic forces that hold the system to the wall, and the gravity force are defined as the parts of the overall disturbance. A well-designed motion controller must be accurate enough to drive the robot's trajectory while also being robust enough to withstand overall disturbances. It must also take into account the limited control signal and saturation related with the servomotors. MATLAB/Simulink is used to identify experimental parameters and simulate various control scenarios.