PI Controller Tuning for a CSTR System with MATLAB

Overview

This repository contains the MATLAB implementation of a project aimed at tuning a Proportional-Integral (PI) controller for a Continuous Stirred Tank Reactor (CSTR) system involving two exothermal series reactions. The goal is to control the reactor's temperature by regulating the cooling water flow using a PI controller. The Ziegler-Nichols method was applied for tuning, ensuring robust control with minimal errors and stability in both servo and regulatory modes.

Key Features

• System Modeling: Developed a dynamic model of the CSTR system, linearized using Laplace transforms.
• Control Objective: Temperature control via cooling water utility in the reactor jacket.
• Tuning Method: Ziegler-Nichols method for controller tuning.
• Error Minimization: Focused on minimizing Integral Squared Error (ISE) and Integral Absolute Error (IAE).
• Simulation Tools: Implemented using MATLAB Simulink and workspace.

Content

• Assignment: Documentation of problem formulation and objectives.
• Report: Detailed analysis, visualizations, and results.
• MATLAB Code: Scripts and Simulink models used in the project.
• Diagrams & Tables: Visualization of system dynamics and control performance.

Files

• /src: Contains all MATLAB and Simulink files used for the project.
• /docs: Full project report and assignment details.

Usage

To run the simulations, download the repository and open the files in MATLAB.

git clone https://github.com/Pouria-MK/_Jan.2024_PI-Controller-Tuning-for-a-CSTR-System-with-MATLAB.git

Ensure that you have MATLAB and Simulink installed on your system.

Conclusion

This project demonstrates an effective approach to temperature control in a CSTR system using a PI controller tuned with the Ziegler-Nichols method. The robust performance, achieved through MATLAB simulations, highlights the system's response stability and error minimization.

Future Work

• Exploration of advanced control strategies (e.g., Model Predictive Control (MPC), adaptive control).
• Integration of real-time optimization techniques.
• Extension to multi-variable control problems.

Contact

For any queries, feel free to reach out via email at pooriamotahari@gmail.com or through GitHub.