PPolySim OS

LQR Control

The optimal way to balance an inverted pendulum. Set your cost weights and watch the Riccati equation hand you the controller that stabilizes a cart-pole.

LQR Control StudioLive

Controls

Balance an inverted pendulum with an optimal controller. The gain K is computed by solving the Riccati equation for your Q/R weights — not hand-tuned. Cheap control (low R) reacts hard; expensive control (high R) acts gently.

Presets

▶ Run in Python

Data Inspector

Gain K[-1.8, -3.2, -38.8, -7.8]
Closed-loop poles-0.74+0.68i
Max Re(λ)-0.74
Stabilitystable ✓
Settling time6.3 s
Peak force14 N
λ = -0.74+0.68i, -0.74−0.68i, -5.45−2.32i, -5.45+2.32i

Governing equation

Reading this result: LQR balances state error against control effort here (R = 0.3): the pole recovers in about 6.3 s with a peak force near 14 N. Lower R to react harder, raise it to act gentler.

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

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How it works

Linear-Quadratic Regulator (LQR) design starts from the cart-pole linearized about its upright equilibrium, ẋ = Ax + Bu. You choose a cost J = ∫(xᵀQx + uᵀRu) dt — Q penalizes state error (cart position and pole angle), R penalizes control effort. The solver finds the gain K = R⁻¹BᵀP by solving the continuous-time algebraic Riccati equation, then simulates the closed loop ẋ = (A − BK)x from a disturbed start. Cheap control (small R) yields an aggressive gain that snaps the pole upright; expensive control (large R) gives a gentle, slower recovery. The closed-loop eigenvalues always land in the left half-plane, so the pendulum provably stabilizes.

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The math, the assumptions, real-world uses, or a code translation — explained for this exact simulation.

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Frequently asked questions

Is this LQR optimal control pole placement tool really free?
Yes. LQR Control runs entirely in your browser using your device's own compute, so local use is free forever. You only pay Compute Tokens if you scale a job to the cloud.
Do I need to install anything?
No. Everything runs client-side in a modern browser — no downloads, no license, no account required to start.
Can I save or share my simulation?
Create a free account to save projects, and use a shareable embed or minted DOI to publish a live, interactive version anywhere.
How accurate are the results?
The solver uses established numerical methods, but results are for research and educational purposes and should be validated against experiment or professional review before you rely on them.