Now that we have covered the línea, come and fill it up, we'll dive into another example to help highlight
how to apply the filter to a system with different characteristics.
We will investigate the pendulum estimation problem in the section.
The pendulum dynamic system is a great example to show that the linear common filter can be applied
to a nonlinear problem if the appropriate considerations and approximations are made inside the filter.
So now let's have a look at the pendulum estimation problem.
We have a simple pendulum system here that has a mass spin it from a pivot point that allows it to freely
swing.
When the mass is released from a non-zero angle, it will swing back and forth.
Our estimation problem will be to how to estimate the state of the pendulum, which consists of the
angle of position theta and the angular right theta dot.
And we're going to do this from a series of noisy measurements of only the angle of the pendulum theta.
So this section of the course is going to break the pendulum problem down into five different videos.
The first video is the pendulum estimation problem.
So that's this video here where be going over what we're actually trying to accomplish in this problem.
The next is going to be the system and measurement dynamics where we talk about the pendulum motion
and dynamics directly.
Next is going to be the common field of model implementation, where we talk about how to model and
implement the common filter for this particular system.
Then we're going to have a look at the tuning and performance of the system that we've just implemented.
And finally, we're going to wrap up with a summary of what we've learned in the section.