Thoughtrons Ctrloop — SISO/MIMO Control Loop Designer

Control Systems · 101

What does a control system actually do?

A control system is the brain that makes a machine do what you want — even when the world is fighting back. Drones holding altitude in a gust. Cars holding speed up a hill. Tank turrets locking on a moving target. Lasers steering a beam. Same idea, every time. Here's the pattern that runs them all.

live block diagram

r → e → u → y · feedback closes the loop

01 · Reference

"Hold this number."

"Stay at 120 km/h." "Hover at 100 m." "Aim at the target." A number, or a moving signal, that the system has to match.

02 · Plant

The machine itself.

Drone. Car. Turret. Reactor. Robot arm. Each has physics — it doesn't react instantly, it has inertia, it needs energy and energy cannot be infinite, it's pushed around by wind, friction, gravity, noise. The "plant" is what you're trying to control.

03 · Controller

The brain you design.

Reads the error (gap between what you want and what's happening), computes the right action, and does it again. 1000 times a second or more. Forever. That's what Ctrloop designs.

Live demos · running in your browser

Real engineering, animated.

Two live simulations of actual control problems engineers solve every day. Drag the disturbance sliders. Watch the controller fight back.

01 · UAV CONTROL

Drone Altitude Hold

live

A quadrotor holding altitude under wind gusts. PID commands thrust to track the setpoint.

Altitude

—

Error

—

Wind

—

K_p2.5

K_i0.80

K_d0.40

Wind1.00

Plant

m·ÿ = u − mg − cẏ + d(t)

Controller

u(t) = K_p·e + K_i·∫e dt + K_d·ė

02 · FIRE CONTROL

Turret Slew & Track

live

A 2nd-order azimuth-axis turret tracking a maneuvering target. Same loop topology — different plant.

Bearing

—

Lead error

—

Slew rate

—

K_p8.0

K_i0.60

K_d1.60

Target speed1.4

Friction0.8

Plant · azimuth axis

J·θ̈ + b·θ̇ = τ

PID with feed-forward

τ = K_p·e + K_i·∫e dt + K_d·ė, e = θ_tgt−θ

These exact problems start as a transfer function in Ctrloop and end as deployable C/Python/MATLAB code.

High-tech, made easy

From envelope to running code, in four steps.

No professional toolbox licensing. No 200-line Python notebooks. You describe your plant; Ctrloop designs the controller; you copy the code and ship it.

STEP 01

Describe the plant

Type a transfer function or paste Bode data. Cascading blocks, expressions with π and √, MIMO 2×2 with cross terms — all valid.

G(s) = 1 / (s² + 0.4s + 4)

STEP 02

Set performance specs

Pick frequency-domain (PM, GM, ω_c) or time-domain (settling, overshoot, rise). Set disturbance & jitter targets.

PM ≥ 60° · ω_c = 4 rad/s

STEP 03

Design

PID, pole-zero placement, or Bode shaping — the iterative engine converges.

C(s) = 4.2 (1 + 1/(0.8s) + 0.12s)

STEP 04

Discretize & export

Tustin / ZOH / Euler. Get the difference equation, ready-to-paste C / Python / MATLAB compatible code, and a one-click DOCX report.

// auto-generated C\nu = 4.2*e + i_acc + 0.12*de;

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Why Ctrloop

What you get that you don't elsewhere.

Plans

Three plans. Pick what fits your work.

Every plan starts with a 7-day free trial — no credit card required. For pricing details, fill the contact form below and we’ll send a tailored quote.

Pricing · Talk to us

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FAQ

Questions, answered.

Anything we missed? Email business@thoughtrons.in and we'll add it.

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Design control loops. SISO. MIMO. Done.