PID control is reactive — it waits for an error to develop, then corrects. Feedforward control is proactive: it measures or predicts a disturbance and pre-compensates before the process variable ever deviates. The two are almost always used together, with feedforward doing the heavy lifting and PID cleaning up the residual.

The core idea: if you know a disturbance is coming and you know how the process responds to it, you can calculate the corrective action in advance. You don't need to wait for the thermometer to drop or the tank level to fall.

Classic example — a steam-heated water heater: cold feedwater enters a tank, steam heats it, and you want the outlet at 80 °C. A pure PID loop on outlet temperature works fine at steady state. But when feedwater flow suddenly doubles, the outlet temperature crashes before the PID even notices, and it takes 30+ seconds to recover.

Add a flow meter on the feedwater. The heat balance is simple:

• Q = ṁ · cₚ · ΔT
• If feedwater flow doubles, the required steam flow must roughly double too.
• The feedforward block computes that steam demand directly from the measured feedwater flow and adds it to the PID output.

Result: when flow jumps, steam jumps simultaneously, and the outlet temperature barely moves. PID only trims the small modeling error.

Where feedforward shines:

• Measurable disturbances — load changes, ambient temperature, upstream flow, batch composition.
• Slow processes with long dead time — anywhere PID alone is too sluggish.
• Known process gains — you must have a decent model relating disturbance to required action.

Real-world examples:

• HVAC: outdoor air temperature feeds forward into chilled-water valve position before the building heats up.
• Paper machines: stock flow measurement adjusts dryer steam before sheet moisture drifts.
• CNC machine tools: velocity and acceleration feedforward in servo drives — the controller knows the commanded trajectory and torques the motor in advance instead of chasing position error.
• Cruise control on hilly roads: a "grade-anticipating" cruise system reads upcoming road incline from GPS and opens the throttle before the car slows.

Rule of thumb: feedforward handles the predictable 80% of a disturbance; feedback handles the unpredictable 20% — measurement noise, modeling error, unmeasured disturbances. Never use feedforward alone; without feedback, any model mismatch causes permanent offset.

The trap: feedforward requires a model. If your process gain changes (fouling, wear, seasonal effects), the feedforward calculation drifts off. Periodic recalibration matters.