SCILAB AS A TOOL FOR DATA ACQUISITION AND PID CONTROL SIMULATION

Abstract

This article discusses the relevance of PID (Proportional, Integral, and Derivative) control in industrial processes that require high precision, fast response, and minimal fluctuations. PID control integrates three operating strategies to ensure system stability and adequate performance, and is widely used in contexts where tolerance to variations is limited. It is important to emphasize that the data acquisition stage is crucial to the success of the control, since failures in data collection, transportation, or analysis can result in inconsistencies, losses, and increased operating costs. As a practical example, the communication between the Arduino AT MEGA 2560 board and Scilab software for signal generation, reading, processing, and visualization is presented, highlighting the importance of a solid database in the development of PID control. The PID system is detailed in its three components: proportional, integral, and derivative, which, together, promote fast response, minimize fluctuations, and reduce error, enabling accuracy close to the established reference value (set point). The study emphasizes that effective implementation of PID control depends on the appropriate use of the functional blocks that make up the controller, compensating for the limitations inherent in each component individually. The main objective of this work is to demonstrate all the steps that precede PID implementation, highlighting its applicability in industrial environments that require robust and reliable control systems.