PID (Proportional–Integral–Derivative) is a control algorithm that continuously calculates and adjusts its output to minimize the difference between a desired set point and the actual process value for stable and accurate control.
🧠 Before We Begin: Key PID Terms
🔸 Set Point
The set point is a user-entered target value.
- For cruise control, it's the desired vehicle speed.
- For a heating system, it's the desired temperature.
🔸 Process Value
The process value is the current value being controlled.
- In cruise control: the actual vehicle speed.
- In a heating system: the current temperature.
🔸 Error
The error is the difference between the set point and the process value. It determines how the controller should react to bring the process closer to the target.
Error = Set Point - Process Value⚙️ Let's Get Dirty: The PID Components
The Proportional term reacts immediately to the error value to reduce the gap between the process value and the set point.
Example:
Kp = 20, Error = 100 → P = 20 × 100 = 2000
This causes the robot to overshoot and turn too hard. The proportional part applies a large correction when far from the target but doesn't know when to stop.
Tuning:
- 🔺 Too High: Causes overshoot (too aggressive correction)
- 🔻 Too Low: Controller reacts too slowly and may become unstable
The Integral term continuously accumulates the error over time until the set point is reached. It helps eliminate steady-state error by adjusting output based on past performance.
It converts accumulated error into a usable correction that fine-tunes the system output.
The Derivative term predicts system behavior by measuring how quickly the error is changing — it acts as a brake to prevent overshooting.
Behavior:
- 🔻 Too Low: Controller may react normally but lacks braking power
- 🔺 Too High: Controller becomes unstable and overreacts to small distortions
🧩 Summary
- P → Reacts to current error (speed of correction)
- I → Reacts to accumulated error (accuracy over time)
- D → Reacts to change in error (stability and braking)
Together, they form a balanced control system capable of precise, stable, and smooth adjustments.
💡 Example Use Cases
- Cruise control systems
- Heating/cooling systems (HVAC)
- Robotics and motor control
- Drones and flight controllers
- Industrial automation
Created by barnoun 🧠 — documenting what I learn so we all get smarter.