PID Control System Simulator
Tune a PID controller driving a simulated DC motor toward a target speed, watch the response live, and feel what each of P, I and D actually does.
Drag Kp, Ki and Kd while the loop keeps running, and watch the process variable chase the setpoint. Try a preset, hit the disturbance, or take the challenge below.
About the PID Control System Simulator
Free pid control system simulator. Tune a PID controller driving a simulated DC motor toward a target speed, watch the response live, and feel what each of P, I and D actually does. Drag, change the sliders and see the result live. No sign-up, works on phone and computer. Built for engineering, the pid control system simulator runs instantly in your browser: change a setting or drag an object and the result updates at once, so you learn by trying things out rather than only reading about them.
Tune a PID controller driving a simulated DC motor toward a target speed, watch the response live, and feel what each of P, I and D actually does. Use it to explore engineering ideas at your own pace, then check what you found against the key ideas further down this page.
How to use the PID Control System Simulator
- Use the controls to change Proportional Kp, Integral Ki, Derivative Kd, Setpoint (target speed), Motor time constant τ. The simulation reacts instantly.
- Pick an option such as D on: error, P only, PI, PID tuned to switch modes or load an example.
- Press "Reset system", "Disturbance / load step" to start, reset or change what is happening.
- Where you see a glowing handle, object, weight or atom, drag it with your mouse or finger. Everything responds in real time.
- Watch the readouts and graphs update as you experiment, and compare what you see with the key ideas below.
Things to try
- Click P only, then slowly raise Kp with the slider — watch the steady-state error shrink but never fully vanish.
- Click PI and watch it reach the setpoint exactly, but with some ringing overshoot on the way there.
- Click PID tuned and compare its rise time and overshoot with the PI preset on the same graph.
- Press the Disturbance / load step button while PID tuned is active, and watch the integral term pull the speed back to the setpoint even under a sustained extra load.
- Try the challenge: tune Kp, Ki and Kd by hand to get under 5% overshoot and settle within 4 seconds, then click Reset system on a fresh setpoint to prove it works from a cold start.
Key ideas you can learn
- A closed loop compares the process variable to a setpoint, computes an error, and feeds a controller output back into the plant, over and over.
- The proportional term (Kp) reacts to how big the error is right now; more Kp means a stronger, faster push but too much causes overshoot and oscillation.
- The integral term (Ki) adds up error over time, so it keeps pushing until the error is completely gone — this is what removes steady-state error, especially under a constant disturbance.
- The derivative term (Kd) reacts to how fast the error is changing, acting like a brake that damps oscillation and reduces overshoot, but too much amplifies noise.
- Integral windup happens when the controller keeps accumulating error while the actuator is already maxed out; clamping the integral term (anti-windup) stops the resulting overshoot and slow recovery.
- Overshoot, settling time and steady-state error are the standard numbers engineers use to judge whether a tuning is good enough for the job.
Where this is used in the real world
Cruise control in cars, thermostats and HVAC systems, drone flight stabilization, industrial process control (temperature, pressure, flow), 3D printer hotends, robotics joint control and power-plant governors all run on PID or PID-like control loops.
Who is this simulation for?
Engineering and technology students, makers, robotics clubs and teachers of design and technology. It gives a hands-on feel for how machines behave before you build a real one.
For teachers: project it on the board, let students predict what will happen, then run it together. For students: change one thing at a time and write down what changes.
Frequently asked questions
Why does P-only control never quite reach the setpoint?
With only a proportional term, the controller output shrinks as the error shrinks, so at some point the output is too small to overcome friction or load — the loop settles with a small permanent offset called steady-state error. Adding an integral term removes it because the integral keeps growing (and pushing) as long as any error remains.
What is integral windup and why does it matter?
If the error stays large for a while (for example right after a big setpoint change), the integral term can build up to a huge value while the actuator is already saturated at its limit. When the error finally crosses zero, that huge accumulated value keeps pushing the wrong way for too long, causing a big overshoot. Clamping the integral accumulator (or the controller output) to a realistic actuator range is the standard fix, called anti-windup.
Why does raising Kd sometimes make things worse?
The derivative term reacts to the rate of change of the error, so it is very sensitive to noisy or jumpy measurements — a real tachometer or thermometer jitters slightly, and Kd amplifies that jitter into a jerky output. In a clean simulation Kd mostly helps, but in the real world engineers usually filter the signal before differentiating it.
Is the PID Control System Simulator free to use?
Yes. It is completely free, with no signup, no download and no ads inside the simulation. It runs in your web browser.
Does the PID Control System Simulator work on a phone or tablet?
Yes. It uses touch as well as the mouse, so you can drag objects with your finger. A larger screen makes the controls easier to see.