activity
20242026
collaborators

12 papers

eess.SY2026

Approximate Feedback Linearization for a Nonlinear Hyperbolic PDE Class -- Part I: Volterra Truncation

Miroslav Krstic

Backstepping for nonlinear PDEs yields exact feedback linearizing laws in the form of infinite Volterra series -- elegant in theory, but with challenges for implementation. This pa…

eess.SY2025

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…

eess.SY2025

Neural Operator Feedback for a First-Order PIDE with Spatially-Varying State Delay

Jie Qi, Jiaqi Hu, Jing Zhang +1

A transport PDE with a spatial integral and recirculation with constant delay has been a benchmark for neural operator approximations of PDE backstepping controllers. Introducing a…

eess.SY2025

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…

math.OC2025

Backstepping for Partial Differential Equations:A Survey

Rafael Vazquez, Jean Auriol, Federico Bribiesca-Argomedo +1

Systems modeled by partial differential equations (PDEs) are at least as ubiquitous as systems that are by nature finite-dimensional and modeled by ordinary differential equations…

eess.SY2025

Delay-adaptive Control of Nonlinear Systems with Approximate Neural Operator Predictors

Luke Bhan, Miroslav Krstic, Yuanyuan Shi

In this work, we propose a rigorous method for implementing predictor feedback controllers in nonlinear systems with unknown and arbitrarily long actuator delays. To address the an…