11 papers
Lotka-Sharpe Neural Operators for Control of Population PDEs
Miroslav Krstic, Iasson Karafyllis, Luke Bhan +1
Age-structured predator-prey integro-partial differential equations provide models of interacting populations in ecology, epidemiology, and biotechnology. A key challenge in feedba…
Sampling-Horizon Neural Operator Predictors for Nonlinear Control under Delayed Inputs
Luke Bhan, Peter Quawas, Miroslav Krstic +1
Modern control systems frequently operate under input delays and sampled state measurements. A common delay-compensation strategy is predictor feedback; however, practical implemen…
Predictor-Based Output-Feedback Control of Linear Systems with Time-Varying Input and Measurement Delays via Neural-Approximated Prediction Horizons
Luke Bhan, Miroslav Krstic, Yuanyuan Shi
Due to simplicity and strong stability guarantees, predictor feedback methods have stood as a popular approach for time delay systems since the 1950s. For time-varying delays, howe…
The Forecast Critic: Leveraging Large Language Models for Poor Forecast Identification
Luke Bhan, Hanyu Zhang, Andrew Gordon Wilson +2
Monitoring forecasting systems is critical for customer satisfaction, profitability, and operational efficiency in large-scale retail businesses. We propose The Forecast Critic, a…
Stabilization of nonlinear systems with unknown delays via delay-adaptive neural operator approximate predictors
Luke Bhan, Miroslav Krstic, Yuanyuan Shi
This work establishes the first rigorous stability guarantees for approximate predictors in delay-adaptive control of nonlinear systems, addressing a key challenge in practical imp…
Delay compensation of multi-input distinct delay nonlinear systems via neural operators
Filip Bajraktari, Luke Bhan, Miroslav Krstic +1
In this work, we present the first stability results for approximate predictors in multi-input non-linear systems with distinct actuation delays. We show that if the predictor appr…