[ewhitman]

A Kalman Filter is not a substitute for a PID. It is something you might do in addition to a PID.

A Kalman Filter attempts to accurately estimate the state (position, velocity, etc.) of your system. It is used either when your sensors are inaccurate (always true to some extent) or when you do not have enough sensors to measure your full state directly.

A KF with even a very crude model can provide more accurate state estimates than reading your sensors directly or traditional filtering if the KF is tuned correctly (not necessarily easy to do). A more accurate system model will result in correspondingly more accurate state estimates.

Extended Kalman Filters allow you to use nonlinear models of your system, which is sometimes desirable, but significantly complicates the process.

I would say that a KF is almost always overkill for FRC applications.

A PID is a control strategy, which means it determines actuator commands (usually motor voltage or duty cycle in an FRC context) based on the system state.