Modern Control in Matlab and Simulink

Welcome to the "Modern Control in Matlab and Simulink" GitHub repository! This repository serves as a resource for exploring various modern control techniques implemented in Matlab and Simulink. The repository is organized into four folders, each focusing on different aspects of control theory.

Contents

1. LQR Control
2. LQG and LQGI Controllers
3. Compensator Design
4. Kalman Filter vs State Space FB Control

LQR Control

The LQR Control folder contains Matlab and Simulink code for the Linear Quadratic Regulator (LQR) control technique. This powerful control strategy is designed to optimize the performance of a system by minimizing a quadratic cost function.

Instructions

• Explore the Matlab code for the implementation of LQR control in Matlab.
• Simulate the behavior of the LQR controller using the provided Simulink model.

LQG and LQGI Controllers

In the LQG and LQGI Controllers folder, you'll find code for both Linear Quadratic Gaussian (LQG) and Linear Quadratic Gaussian Integral (LQGI) controllers. These controllers combine optimal control (LQR) with state estimation (Kalman filter) to enhance system performance.

Instructions

• Check out the Matlab code for the implementation of LQG and LQGI controllers in Matlab.
• Use the Simulink models to simulate the behavior of these controllers.

Compensator Design

The Compensator Design folder focuses on compensator design techniques in control systems. This includes the design of compensators to improve stability, transient response, and overall system performance.

Instructions

• Review the Matlab code for various compensator design techniques.
• Experiment with the provided Simulink models to visualize the effects of different compensator designs.

Kalman Filter vs State Space FB Control

The Kalman Filter Vs State Space FB Control folder compares the performance of Kalman filtering and State Space feedback control. Explore the implementation in Matlab and simulate the behavior in Simulink.

Instructions

• Examine the Matlab code for Kalman filtering and State Space feedback control.
• Utilize the Simulink models to observe and compare the behavior of these techniques.

Contributing

If you find any issues, have suggestions for improvements, or want to contribute additional examples, feel free to contribute! Fork the repository, make your changes, and submit a pull request.

License

This project is licensed under the MIT License, encouraging collaboration and sharing.

Feel free to explore the project, experiment with the code, and adapt it to your needs. Happy exploring! 🚀