Comparing Closed Loop Methods
| Method | Corrects | Weakness | Typical FRC use |
|---|---|---|---|
| P only | Proportional to current error | Permanent steady-state error | Quick, rough position holds where a small error doesn't matter |
| PD | Error, damped by its rate of change | Still has steady-state error | Fast-moving mechanisms where overshoot is worse than a small final offset |
| PI | Error, plus its full history | Overshoot, risk of integral windup | Mechanisms needing zero steady-state error, without needing to be fast |
| PID | Error, its history, and its rate of change | Three gains to tune instead of one | General-purpose position and velocity control |
Every method in this table is built from the same three ingredients covered throughout this section, proportional, integral, and derivative response to error, just weighted differently depending on which terms are in play.
Where This Leads Next
A well-tuned closed loop is very good at reaching a setpoint accurately. It says nothing about what that setpoint should be doing over time, jumping straight to a final target and letting the controller fight its way there produces exactly the fast, jerky, overshoot-prone motion the gain tradeoffs in this section keep warning about. Shaping a smoother path for a closed loop to follow, instead of a single abrupt target, is the subject of Motion Profiling.