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Research questionHow can model predictive control remain feasible and stable for nonlinear systems with intermittent state measurements?When measurements disappear, prediction uncertainty accumulates and measurement-triggered resets can disrupt state propagation. These effects make it difficult to preserve constraints and closed-loop guarantees during feedback outages.
Machine Learning
Research Paper
Robotics
Technology
Latest papersRecent research connected to this question, newest first.Koopman-Based Robust Model Predictive Control for Nonlinear Systems with Stochastic Intermittent MeasurementsThe work studies constrained nonlinear systems with stochastic intermittent state measurements using a Lipschitz-constrained deep Koopman predictor and a two-mode Markov measurement model. It supplies sufficient conditions for mean-square error boundedness, recursive feasibility, and closed-loop regulation, with numerical evidence from a visual-servoing tracking task.research paper · Sep 2, 2026
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