Oséias D. Farias

Integral windup is one of the most common failure modes in deployed PID controllers. This post covers the problem from first principles, derives the back-calculation anti-windup scheme, shows how Synapsys implements it, and validates the design against a simulated second-order plant.

MIL → SIL → HIL is the standard V-model progression for embedded control: simulate everything first, then replace the plant model with real hardware one layer at a time. In most frameworks this requires rewriting large parts of the control loop. In Synapsys the transition is a one-line swap because the transport layer is fully abstracted from the algorithm.

A quadrotor has four rotors, six rigid-body degrees of freedom, and fully coupled rotational dynamics — it is the MIMO benchmark of aerial robotics. This post walks through the complete design pipeline: physics → linearisation → LQR → Neural-LQR residual → 3D simulation.

The inverted pendulum is the canonical benchmark of nonlinear control — unstable, simple enough to model analytically, yet rich enough to reveal the full LQR design workflow. This post derives the linearised model from physics and shows how to stabilise it with Synapsys in a few dozen lines of Python.

Welcome to the Synapsys Blog — a space dedicated to practical control systems engineering, academic research, and real-world applications of the Synapsys library.