Abstract
This article presents the implementation of a learning environment for the teaching of control systems. This environment integrates physical equipment and simulation, monitoring, and control through a network. A software platform based on ROS (Robotic Operating System) grants access to the system through intranet and Internet, facilitating the integration of new test equipment. The environment developed can be used in didactic experiences both inside and outside the classroom, enhancing the learning of four main study topics: modeling, analysis, parameter estimation, and controller design.
Highlights
Automatic control systems are essential in modern life
To implement a learning environment that facilitates the study of the inverted pendulum system, physical components and the Robotic Operating System (ROS) software environment are integrated by means of a data acquisition and a control interface developed by Arduino, which is connected to the intranet as a node
The software package ROS, a middleware well known in robotics, has been used to implement a learning environment for the teaching of control systems in engineering programs
Summary
Automatic control systems are essential in modern life. Air conditioning at workplaces as well as the provision of drinking water and energy, transportation, communications, and the most varied industrial processes all require automatic control systems to achieve efficiency, reliability, and safety. Traditional systems are studied from a mathematical perspective and students are given tasks to compare theoretical results and measurements in real or simulated systems In these tasks, well-designed equipment is key for demonstrations and didactic activities [1,2,3,4,5,6]. In [20], a deep learning-based pipeline smart system is developed, which is able to recognize block diagrams from control systems with handwritten feedback control architectures in a whiteboard and transforms them automatically into simulation diagrams in the MatLab software In this way, the control system is visualized, executed, and analyzed in an interactive way using MatLab. In [21], a new teaching method for robot control systems called AVPC (Algorithm, Virtual experiment, Programming, and Controller) is presented.
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