Submitted · IEEE Trans. Control Systems Technology · 2026

Quantum-Transport
Informed Digital-Twin MPC
for Metal-Hydride
Hydrogen Storage

Bridging microscopic hydrogen-tunneling physics with macroscopic predictive control — multiscale modeling and formal guarantees.

IEEE TCST · Under Review
01 — Synopsis

A unified framework for quantum-aware hydrogen control.

Classical metal-hydride (MH) hydrogen-storage systems exhibit inherently slow absorption/desorption dynamics that worsen at low temperatures ($T \lesssim 200\,\mathrm{K}$), where quantum-mechanical transport effects — hydrogen tunneling and zero-point lattice vibrations — sustain measurable diffusion that classical Arrhenius kinetics cannot predict, causing systematic actuation bias and degraded closed-loop performance.

This work presents a quantum-transport-informed MPC framework with a parameter-level digital-twin estimation architecture, in which a temperature-dependent quantum correction factor $g_q(T)$, grounded in zero-point energy theory, augments the classical Arrhenius law and is propagated through a multi-fidelity hierarchy into the MPC prediction matrices, enforcing a physics-consistent parameter manifold $\Theta$ at every online weighted least-squares update.

Physics-calibrated simulations on the authors' LaNi$_5$-H$_2$ platform demonstrate 70.2% settling-time reduction over classical MPC and 50.0% over the authors' prior LARC, with complete overshoot elimination at $120\,\mathrm{K}$ and a zero-overshoot safety benefit persisting across the full operating range $(298$–$333\,\mathrm{K})$.

Classical MPC believes the plant is slow.
The true quantum plant is faster.
The mismatch is structural — not curable by retuning.
02 — Contributions

Four contributions, theoretical and numerical.

01
Quantum-Informed Diffusion Model

Temperature-dependent correction factor $g_q(T)$, grounded in zero-point energy theory, augments the classical Arrhenius law for control-ready effective diffusion.

Section II-B
02
Physics-Consistent Estimation Architecture

Microscopic quantum transport parameters propagate into macroscopic MPC prediction matrices via a multi-fidelity hierarchy, enforcing the manifold $\Theta$ at every update.

Section III-B
03
Robust Estimation, Formal Guarantees

Huber-WLS regression identifies $[\mathcal{D}_0, E_a]^\top$ from noisy, sparse data. Lemma 2 proves $\mathcal{O}(N^{-1/2})$ bootstrap confidence-interval convergence.

Algorithm 1 · Lemma 2
04
Stability & Provably Positive Advantage

Theorem 1: asymptotic stability with explicit exponential rate. Corollary 1: closed-form excess-cost bound — classical MPC's penalty is strictly positive at all finite $T$ and diverges as $T \to 0^+$.

Theorem 1 · Corollary 1
03 — Theory

Two results, anchored by physics.

Theorem 1 · Closed-Loop Stability
Asymptotic stability with explicit exponential rate.

Under Assumptions (A1)–(A3), the closed-loop system satisfies recursive feasibility, monotone Lyapunov decrease, and $\hat{c}_k \to r$ with rate determined by the physical bounds of $\Theta$.

$|\hat{c}_k - r|^2 \le \dfrac{V_0^\star}{\lambda_{\min}(Q)} \left(1 - \dfrac{\lambda_{\min}(Q)}{\lambda_{\max}(P)}\right)^k$
Corollary 1 · Performance Advantage
Closed-form lower bound on classical MPC's excess cost.

Let $\delta_k \triangleq \mathbb{B}_q(T_k) - \mathbb{B}_c(T_k)$. Then $J^{\mathrm{class}}_k - J^{\mathrm{quant}}_k \ge 0$ with strict inequality for all finite $T_k$. The relative mismatch grows without bound as $T \to 0^+$.

$\dfrac{\delta_k}{\mathbb{B}_c(T_k)} = \exp\!\left(\dfrac{g_0}{R_g}\cdot\dfrac{e^{-T_k/\lambda}}{T_k}\right) - 1$
04 — Results · T = 120 K

The performance gap — measured.

At $T = 120\,\mathrm{K}$ (deep cryogenic, $D_{\mathrm{ratio}} = 4.23\times$), the quantum-informed controller produces a transient that classical Arrhenius-based MPC cannot match by any choice of weights.

Three controllers operate on the same true quantum plant: classical MPC, the authors' prior LARC (IEEE TIE 2022), and the proposed quantum-informed MPC. The zero-overshoot safety benefit holds across the full operating range $(120$–$333\,\mathrm{K})$, not only the cryogenic regime.

The advantage stems from the physics-consistent diffusion model, not from the MPC architecture alone — confirmed directly by Experiment 7 (Corollary 1 validation).

Closed-loop @ T ≈ 120 K
Settling time, classical MPC 5.7 s
Settling time, LARC [22] 3.4 s
Settling time, quantum (ours) 1.7 s
Overshoot reduction 100%
$t_s$ improvement vs. classical 70.2%
05 — Validation

Eight experiments, mapped to theory.

EXP · 01
Baseline WLS
Lemma 2
EXP · 02
Outlier Robustness
Huber–WLS
EXP · 03
Data Sparsity
$\mathcal{O}(N^{-1/2})$ CI
EXP · 04
Quantum Diffusion
Lemma 1
EXP · 05
Model Fidelity
Multi-fidelity DT
EXP · 06
Closed-Loop Sweep
Theorem 1
EXP · 07
Cost Gap
Corollary 1
EXP · 08
Time-Varying T
Online robustness
06 — Platform Continuity

A decade on the same LaNi$_5$ platform.

This work is the third in a series advancing control methodology for the authors' LaNi$_5$-H$_2$ experimental platform. The hardware-in-the-loop campaign currently in preparation will deploy the proposed framework on the same hardware that already validated our prior controllers.

2013 / 2014
Fuzzy adaptive PID control
MH reactor coupled with thermoelectric module (J. Bionic Eng.; IEEE/ASME AIM).
2022
LARC — Learning-based Adaptive Robust Control
Sliding-mode adaptation on the same platform (IEEE Trans. Industrial Electronics).
2026 · This work
Quantum-Transport-Informed Digital-Twin MPC
Physics-grounded multiscale framework with formal stability and performance guarantees (submitted IEEE TCST).
Next
Hardware-in-the-loop deployment
INS / DFT identification of $g_0, \lambda$ for LaNi$_5$; transient performance validation against simulation.
07 — Paper & Code

Read, cite, reproduce.

Preprint

Full manuscript currently under review at IEEE TCST. Open access on Preprints.org.

View →
Code

Implementation in Julia 1.12 with OSQP and JuMP.jl. Repository release accompanies the camera-ready paper.

Julia · OSQP · JuMP
Cite

Nuchkrua, T., Boonto, S., Liu, X.
"Quantum-Transport-Informed Digital-Twin MPC for Metal-Hydride Hydrogen Storage."
Submitted, IEEE TCST, 2026.

BibTeX coming soon