How often, and how long, should a digital twin be re-identified as the plant drifts?

research/twin-recalibration

Re-identifying a drifting twin by dedicated experiments: closed-form interval T*∝q_d^{−2/3} with downtime, noise and drift regret exactly equal at the optimum, excess ∝q_d^{1/3}, a 4× drift misjudgement costs ≤26%, but the second-order optimum destabilises 0.7–15% of cycles and a safe schedule is 37–200× worse than an always-on Kalman twin.

10 tests

What it found

For a twin refitted from dedicated experiments rather than filtered from operating data, the second-order-optimal schedule is closed-form: interval T* = (4cσ²/(vρq_d²))^1/3, with experiment downtime, estimation noise and drift regret exactly equal at the optimum, so excess cost scales as q_d^1/3 (fitted slope 0.333) and 10× cheaper experiments lower it only 2.2×. Misjudging the drift rate by 4× costs at most 26%. But the second-order optimum is unsafe: 0.7–15% of its cycles destabilise the loop, and a schedule with failure probability ≤ 10⁻³ costs 1.2–16× more and is 37–200× worse than an always-on Kalman twin. Stylised.

A figure from its own output

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

Paper, code and results

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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.