Is this good for educators?

Yes — this version of "Cart-Pole Control Design for a soft robot" is framed for educators teaching it to a class. Drop a live demo into a lecture or assign it as a shareable link — no lab installs.

Do I need to install anything?

No. It runs in any modern browser, free, with no account required.

For Educators · Cart-Pole Control Design

Cart-Pole Control Design for a soft robot

Built for educators teaching it to a class. Drop a live demo into a lecture or assign it as a shareable link — no lab installs. Simulate a soft robot live below — adjust the inputs and watch it respond, right in your browser.

Cart Pole

open full solver →

Cart-Pole BalanceLive

inverted pendulum control

Controls

Speed1×

Presets

Controller gain

Disturbance

Controller on

Balancing a pole on a moving cart is the classic control benchmark. A state-feedback controller senses the pole angle and cart position and pushes the cart to keep the pole upright. Turn the controller off and it topples instantly; add disturbance to test how hard it can fight back.

▶ Run in Python

Data Inspector

Pole angle8.6°

Cart position0.00

Statusbalanced

Governing equation

F = - K x = 1.0 (55 θ + 12 \dot{θ} + 1.5 x + 3 \overset{x}{˙})

Reading this result: The state-feedback law F = -K·state pushes the cart under the falling pole; with gain above the disturbance it recovers from each nudge.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

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PID Control

open full solver →

PID ControllerLive

step response tuning

Controls

Presets

Proportional Kp

Integral Ki

Derivative Kd

A PID controller drives a system to its setpoint using three terms: proportional reacts to the current error, integral eliminates steady-state offset, and derivative damps overshoot. Tuning the three gains trades off speed, overshoot, and stability — the workhorse of industrial control.

▶ Run in Python

Data Inspector

Overshoot0%

Settling time0.00 s

Steady-state error0.000

Governing equation

u (t) = 4.0 e (t) + 1.00 \int e d t + 0.5 \frac{d e}{d t}

Reading this result: Balanced gains — proportional for speed, integral to remove offset, derivative to damp overshoot: the textbook well-tuned response.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

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Also for:Students Researchers Engineers Hobbyists & Makers K-12 Students First Responders General version →

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Frequently asked questions

Is this good for educators?: Yes — this version of "Cart-Pole Control Design for a soft robot" is framed for educators teaching it to a class. Drop a live demo into a lecture or assign it as a shareable link — no lab installs.
Do I need to install anything?: No. It runs in any modern browser, free, with no account required.