Abstract
This paper presents the development of a new Aerodynamic Ball Levitation Laboratory Plant at the Center of Modern Control Techniques and Industrial Informatics (CMCT&II). The entire design process of the plant is described, including the component selection process, the physical construction of the plant, the design of a printed circuit board (PCB) powered by a microcontroller, and the implementation of its firmware. A parametric mathematical model of the laboratory plant is created, whose parameters are then estimated using a nonlinear least-squares method based on acquired experimental data. The Kalman filter and the optimal state-space feedback control are designed based on the obtained mathematical model. The designed controller is then validated using the physical plant.
Highlights
The core principle of aerodynamic levitation is based on suspending an arbitrary object in the air using airflow
Similar to the Magnetic Levitation Plant, which uses a magnetic force to levitate a steel ball [2], the Aerodynamic Levitation Plant could be a part of control engineering courses provided by the Center of Modern Control Techniques and Industrial Informatics (CMCT&II) at the Department of Cybernetics and Artificial Intelligence (DCAI), Faculty of Electrical Engineering and Informatics (FEEI), Technical University of Košice (TUKE)
The main goal of this paper is to present obtained experimental results from the newly created Aerodynamic Ball Levitation plant
Summary
The core principle of aerodynamic levitation is based on suspending an arbitrary object in the air using airflow. The practical use-case of this phenomenon can be seen in applications where physical contact between objects must be avoided. It is usually utilized on a microscopic scale to prevent oxidation or crystal formation upon object contact with its container. The main advantage of the Aerodynamic Levitation Plant over the Magnetic Levitation Plant is its slower dynamics. It allows the use of a larger sampling period and more computationally expensive control algorithms. This model provides a wider ball position operation range that makes experimental identification simpler
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