IEEE Control Systems Letters · 2026
VigilMPC: Certified Online Tube Model Predictive Control for Safe Real-Time Neuromodulation
IEEE Control Systems Letters
Can a predictive controller safely update its learned dynamics online?
VigilMPC accepts a predictor update only when a backup plan remains feasible under tightened constraints. Recursive feasibility and constraint satisfaction follow under the tube MPC assumptions. Evaluation uses simulated neural dynamics and a switching benchmark, rather than clinical deployment.
Research themes
Connections
From language context to constrained actions
INSTRUCT MPC translates human instructions into disturbance predictions. World model certification and VigilMPC study complementary ways of deciding which learned models can support reliable planning and safe updates.
Open questions
Certified contextual control
Can contextual and world model updates be certified before they affect a physical system?
Explore open directionsCite this paper
Yu Mao, Zhichao Liang, Junxiang Zhang, Quanying Liu, Tongxin Li. VigilMPC: Certified Online Tube Model Predictive Control for Safe Real-Time Neuromodulation. IEEE Control Systems Letters, 2026. https://doi.org/10.1109/LCSYS.2026.3711599
BibTeX
@article{tongxin-vigilmpc,
title = {{VigilMPC: Certified Online Tube Model Predictive Control for Safe Real-Time Neuromodulation}},
author = {Yu Mao and Zhichao Liang and Junxiang Zhang and Quanying Liu and Tongxin Li},
year = {2026},
journal = {IEEE Control Systems Letters},
url = {https://doi.org/10.1109/LCSYS.2026.3711599},
doi = {10.1109/LCSYS.2026.3711599}
}
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