CLab
Description
A remote-controlled experimental kit designed for studying heat transfer, temperature regulation, and dynamic barrier control. Integrates ESP32 microcontroller, sensors, actuators, and a MATLAB-based interface for real-time monitoring, PID control, and data visualization.
Objective
To study heat transfer dynamics, temperature control, and motorized barrier regulation through a real-time, remotely controlled experimental platform.
Method
The system uses an ESP32 microcontroller to collect sensor data, control actuators, and communicate via JSON. Users interact through a MATLAB-based interface to set parameters, start experiments, and visualize results.
Practical Applications
Thermal management system design, PID control validation, energy transfer analysis, smart automation, and mechatronics system integration.
Key Features
Remote real-time control and monitoring PID-based temperature and motor control Motorized adjustable barrier Embedded system with WiFi connectivity MATLAB App integration for user interaction and data visualization
Learning Outcomes
Understanding of thermal-fluid dynamics and heat transfer Application of PID control principles on real systems Development of skills in embedded programming and remote experimentation Experience in real-time data acquisition and analysis
Functional In/Out Diagram
The functional diagram above illustrates the main components of the system and their interactions:
Input: User-defined experiment parameters (lamp power, fan control, PID coefficients, barrier position) Environmental conditions (initial chamber temperatures) Real-time sensor readings (temperature sensors, potentiometer position sensor)
Process: The ESP32 processes input parameters and real-time sensor data. Executes PID control algorithms for temperature and motor regulation. Adjusts actuator outputs (lamp intensity, fan speed, motor position) accordingly. Collects and logs experimental data at defined sampling intervals.
Output: Controlled physical responses (heating, cooling, barrier movement) based on user inputs and system feedback. Real-time data streams (temperature evolution, motor position, control signals) available via JSON. Visualizations and downloadable experiment results through MATLAB App.