Skip to content

Event

Dissecting State-Space Design and Inverted-Pendulum Closed Loop with python-control

1 reports · 1 sources

A technical article using python-control as its tool, dissecting the complete workflow of state-space control design: using controllability and observability criteria to determine system properties, using pole placement and LQR (algebraic Riccati equation solution) to design controllers, and presenting treatment approaches for dual observers and frequency-domain margins. The article further deploys discrete LQR and an energy-based swing-up strategy into a closed-loop simulation of a MuJoCo cart-pole inverted pendulum, grounding the above design methods in a concrete physical scenario. The report does not provide measured results or performance data for this closed-loop scheme.

Report timeline

  1. python-control: State-Space Design and the Physical Closed Loop of an Inverted Pendulum

    Using python-control as the vehicle, the article breaks down state-space control design, covering controllability and observability criteria, pole placement, the algebraic Riccati solution for LQR, the dual observer, and frequency-domain margins. It also deploys discrete LQR and an energy-based swing-up strategy into a MuJoCo cart-inverted-pendulum closed loop.

    Guyuehome ·

Related topics

Motion controlSoftware and compute systemsGuides and practice

Interest trend

Current
3
Peak
7Nov 4 01:00
Past 24 hours
-50%

The trend compares participants observed throughout the same period, so its range may be smaller than the current interest count. Move or tap to inspect each hour; use the arrow keys on a keyboard.