← All projectsGitHub
Digital twins & sim-to-real

Does a twin that models each axis alone certify gains that actuator coupling destabilises?

research/coupling-twin

A per-axis twin of a two-axis loop certifies gains that actuator coupling destabilises: stable-gain limit 2/(1+√p) not 2 (a 10% margin fails at c=1/9), twin-deadbeat rate is √|p| not 0, and a fitted diagonal gain 1+cρ depends on log correlation while the full fit's variance grows as 1/(1−ρ²).

9 tests

What it found

For a two-axis loop x’ = x − kGx with cross-gain c, the stable-gain limit is 2/(1+√p) (p=c12c21≥0) or 2/(1+|p|) (p<0) instead of the twin’s 2, so a twin-certified 10% margin (k=1.8) fails at c=1/9, and no positive gain is stable once √p≥1. The twin-deadbeat gain has real rate √|p|, not 0 (6–270 steps to 10−6 for c=0.1–0.95 vs 1). A diagonal gain fitted from logs is 1+cρ for input correlation ρ (Monte Carlo matches to four digits), giving real rate c(1+ρ)/(1+cρ) (0.300 at ρ=0, 0.461 at ρ=1); the unbiased full fit has variance ∝ 1/(1−ρ2) (verified within 5%), so near-collinear logs make coupling unidentifiable while the per-axis fit returns a confident wrong gain. Follow-up to the control twin. Stylised: linear constant coupling, two axes, noiseless plant.

A figure from its own output

Figure produced by research/coupling-twin: stable_gain
coupling-twin/experiments/stable_gain.svg, written by the project's own experiment code.

Paper, code and results

More in Digital twins & sim-to-real

All 164 Digital twins & sim-to-real projects →

Other research topics

Proper scoring & elicitation28Effort & peer prediction9Verification games & slashing19Detection & tolerances14Markets as routers13Prediction-market design9Paying contributors8Decentralised training systems23Digital twins & sim-to-real164LLM chip design loops40Robot manufacturing loops53Ambient AI assistant46Self-replicating manufacturing34Simulation-first design64Engineered clothing45Task-specific AI accelerators40Algorithmic chip-design loops42Open-source purpose-built robots44The software-engineering loop43Adversarial human imitation41Open-source residential construction41Autonomous multi-angle capture34Sensing, imaging and 3D31Energy supply and dense energy storage39Robot societies among people31Agentic co-design of low-cost robots27Laundry-hanging robots25Machine learning on qualitative data23Robots on the building site27Civilizations & group psychology1History & human sciences1

Produced with AI assistance (Claude). Results are from the code in this repository and are simulated or stylised unless the abstract says otherwise; nothing here implies affiliation with or endorsement by any lab, researcher or company cited. MIT licensed.