Kalman filtering is a powerful technique for estimating the state of nonlinear mechatronics systems from noisy measurements. Kalman filters have a wide range of applications in robotics, vehicle control, and aircraft control.
Pendulum Control with Kalman Filter is a MATLAB project for controlling and stabilizing a simple pendulum system using a Kalman filter. This README provides a brief overview of the code and how to get started.
The code presented here is designed to estimate the angular position of a pendulum using a state-space formulation and a Kalman filter. It is a great resource for learning about filtering techniques.
Here's a quick overview of the key components:
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Pendulum Parameters: The initial parameters of the pendulum, including gravitational acceleration (
g), arm length (l), mass (m), sample time (Ts), and initial conditions (x_0) for angular position and velocity. -
State Space Formulation: The state-space representation of the pendulum system is defined with matrices A, B, C, and D. These matrices are used to model the dynamics of the pendulum.
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Kalman Filter: This code also includes parameters for the Kalman filter, such as process noise covariance (
Q) and measurement noise covariance (R).
To start using this code and experiment with the control of the pendulum, follow these steps:
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Clone the Repository: First, clone this repository to your local machine.
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Open and Run in MATLAB: Open MATLAB script Inverted_Pen.m.
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Open and Run the SIMULINK: Open the SIMULINK design invert_pend.slxc, and you can start running and experimenting with the pendulum model.
Feel free to modify the code and experiment with different pendulum parameters or other filtering strategies. The LaTeX docuumentation provides a solid foundation for learning and exploring the world of state estimation.
If you'd like to contribute to this project, please feel free to fork the repository and submit a pull request with your improvements. We welcome contributions from the community!
- Thanks to the open-source community for valuable resources and inspiration, especially the MATLAB tutor https://bit.ly/3i4VKwG.
Have fun experimenting with the pendulum estimation project! If you have any questions or need assistance, please don't hesitate to contact me at solomon.nwafor@unn.edu.ng.
Thanks