[jee7s]

The Kalman filter probably isn't something you'd really be ready to handle in HS.

I'm getting a Doctorate in controls, so let me see if I can put the KF in more understandable terms...

Basically, the Kalman filter finds an optimal estimator in a noisy environment, but there's a lot you'd have to know before you get to that.

First off, controls (meaning the mathematical treatment of it) takes a lot of math. I mean Differential Equations, Laplace Transforms, matrices, state space, etc. These concepts don't come up until at least a second year in college, typically. Usually students encounter controls as a fourth year engineering student, and the Kalman filter is beyond that. Personally, I didn't come across the KF until I was a second year in Grad. School.

In advanced controls, the focus isn't on the input and output...it's about what's going on inside. We call this the "State" of the system. The state can't always be measured (think about how many sensors it would take to know the acceleration, speed, and position of a wheel mounted on a motor). But, there's a little trick...if you know how the system you're working with behaves (in this case a wheel mounted to a motor), you can "estimate" the state by knowing only a small part of it.

In the case of a wheel mounted to a motor, the state is the angular speed, angular position, and current through the motor. These could all be measured, but that isn't always possible.

But, using an Estimator or Observer (the same thing) mentioned above, if you know the position, you can find an approximation of the full state. However, noise can be a problem, and the Kalman filter overcomes this by taking features of the noise, combined with features of the system to find an optimal estimator. To create one, you need to know the noise of the input, the noise of the state (noise in the system), and how the two are related to each other and within each other. I won't go any further, because at this point we get into all sorts of matrix math and probability theory that I don't want to get into at midnite.

It could be implemented for FRC, but it may not be necessary. As I have heard it put: don't use a sledge where you need a finishing hammer..it doesn't look good.

If you want to pursue KF, then I'd suggest learning about lower level controllers, like PID and Lead/Lag (WHY they work, not just how to use them), and build up to it.

Don't take this as discouragement. I hope you find plenty of fascinating control topics to study.

-Jeff Erickson, FRC 41 Mentor

P.S. if you want a book reference, check out Digital Control System Analysis and Design by Phillips and Nagle.