Kalman filter of a mass-spring-damper system

This code repository shows how to design and evaluate a Kalman filter based on a 2DoF mass-spring-damper system.

There are three files about Kalman filter on a 2DoF mass-spring-damper system. You can find description for this simple system here: http://www1.aucegypt.edu/faculty/mharafa/MENG%20475/2DOF%20Systems%20Fall%202010.pdf. Or just google mass-spring-damper system, I am sure that there are plenty of explanations.

Code 'comparison_c_d.m' teaches you how to discretise a continuous state-space model into a discrete state-space model and discuss the effect of sample time, since some of you may confuse (at least I did at first) whether the model should be continuous or discrete when using a Kalman filter.

Code 'kalman_filter_example_c.m' designs a Kalman filter on the system. All the state-space models in this code are continuous and the commands for designing Kalman filter are for continuous systems.

Code 'kalman_filter_example_d.m' designs a Kalman filter on the system. All the state-space models in this code are discrete and the commands for designing Kalman filter are for discrete systems.

The reason I wrote two Kalman filter codes for both continuous system and discrete system is that it is easy for a beginner (as I was) to get lost in deciding whether should I use the continuous model ,where should I discretise my model or which commands should I use. I hope this series of codes will clear your confusion.

Comments in the codes are detailed and you are welcome to ask questions.