First, about open sourcing your code. Kevin Watson has asked that his code not be redistributed, so be mindful of that.
For control algorithms, etc, the most important one to understand is PID control, though practically speaking most FRC mechanisms only need P or PD control.
These whitepapers should prove helpful for that.
The (not-so) brief summary for PID control is that it works like your cruise control works. You pick a set point (cruising speed). The PIC compares this setpoint to feedback it gets from the real world (speedometer). If they don't agree, the PIC applies a control signal in the appropriate direction to correct. In a cruise control, if your actual speed is too slow, it hits the gas. Too fast, it lets off the gas. The algorithm simply multiplies the error by a constant gain and sets the output to this, and you have Proportional control. The remaining terms don't apply directly to cruise control, buuuut... If you were climbing a mountain/left the tire chains on/were dragging a boat anchor, then your car would consistently have an error, since you have to apply SOME gas to over come this, and when you hit your set point, you're applying 0 gas. So you integrate the error as time goes on, multiply by a gain, and add this to your P term. The longer you're missing your set point, the bigger this term, and the more you correct. Integral control. Finally, there's Derivative control. You monitor how fast the error is changing, multiply by a gain, and add. The purpose here is to slow down a rapidly correcting system so that it doesn't overshoot its target.
And all that is covered in more detail with better examples in those white papers. Encoders are opto-electrical devices that you can use to determine the position or speed of a shaft, so you can use them for the feedback. You can also use potentiometers, inductive or ultrasound sensors, photo-resistors, or whatever else is appropriate for what you're interested in controlling.
Finally, to end my last long winded post of the night, I'd highly recommend reading up on state-machines as mentioned in
this presentation. It's a highly useful technique for autonomous programming. Especially with the hybrid mode this year.