AI RESEARCH
Sampling-Horizon Neural Operator Predictors for Nonlinear Control under Delayed Inputs
arXiv CS.LG
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ArXi:2603.29119v1 Announce Type: cross Modern control systems frequently operate under input delays and sampled state measurements. A common delay-compensation strategy is predictor feedback; however, practical implementations require solving an implicit ODE online, resulting in intractable computational cost. Moreover, predictor formulations typically assume continuously available state measurements, whereas in practice measurements may be sampled, irregular, or temporarily missing due to hardware faults.