PID Controller Tuning Lab Community
Questions, answers and tips from people who use the PID Controller Tuning Lab. Tune proportional, integral and derivative gains on a real first-order plant, watch the closed-loop step response redraw with a sweeping time marker, and read off the true overshoot, settling time and steady-state error..
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This page shows only real posts from real people, so it starts empty. The guide below has the questions people most often have about the PID Controller Tuning Lab. Pick one to start a thread, or write your own.
From the tool guide: common questions about PID Controller Tuning Lab
The items below are not posts by community members. They come from the written guide for this tool and are here to get a conversation started. Use “Ask a follow-up” to open a thread about any of them.
Why does proportional control alone almost always leave a steady-state error on this kind of plant?
With pure proportional control, the controller output is u=Kp·e, and at steady state y settles wherever e becomes just small enough that Kp·e·K exactly balances the plant's natural decay - since e can never reach exactly zero without a control action to sustain it, a permanent offset (steady-state error) remains unless integral action is added to keep pushing once error is small.
From the tool guide Ask a follow-upWhy can adding too much integral gain actually make the response worse instead of better?
Integral action keeps accumulating even while the output is overshooting toward the setpoint, so by the time the output arrives at the setpoint the accumulated integral term is still pushing it further, causing it to overshoot and then have to unwind that same accumulated term before it can settle - producing larger overshoot and a longer, more oscillatory settling process.
From the tool guide Ask a follow-upKey ideas
- A PID controller drives a plant using u = Kp·e + Ki·∫e dt + Kd·de/dt, where e is the error between setpoint and measured output.
- Raising Kp alone speeds up the response and shrinks steady-state error, but too much Kp causes overshoot and eventually oscillation.
- Integral action (Ki) is the only term that can drive steady-state error to exactly zero, because it keeps accumulating as long as any error remains - but too much Ki adds overshoot and lag ('integral windup').
- Derivative action (Kd) reacts to the rate of change of error, adding damping that can reduce overshoot from aggressive Kp or Ki - but too much Kd amplifies any noise in the measurement.
Things to try
- Try the well-damped challenge: overshoot below 10%, settling time below 10 s.
- Try the integral-action challenge: steady-state error below 1% while keeping overshoot below 25%.
- Push Kp very high alone and watch the oscillation grow.
- Add derivative gain to tame an overshoot without giving up speed.
Where this is used
Control engineers tune exactly these three gains on real temperature loops, flow loops, motor speed controllers, drone stabilization and robotic arm position control, balancing response speed against overshoot and steady-state accuracy.
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