most citedKoopman Data-Driven Predictive Control with Robust Stability and Recursive Feasibility Guarantees

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SY2025

Offset-free Data-Driven Predictive Control for Grid-Connected Power Converters in Weak Grid Faults

Ivo Kraayeveld, Thomas de Jong, Mircea Lazar

Grid-connected power converters encounter significant stability challenges during weak grid faults, when conventional PI-based controllers exhibit an oscillatory response and poor…

math.OC2025

Deep Operator Neural Network Model Predictive Control

Thomas Oliver de Jong, Khemraj Shukla, Mircea Lazar

In this paper, we consider the design of model predictive control (MPC) algorithms based on deep operator neural networks (DeepONets). These neural networks are capable of accurate…

math.OC2025

A Kernelized Operator Approach to Nonlinear Data-Enabled Predictive Control

Thomas de Jong, Siep Weiland, Mircea Lazar

This paper considers the design of nonlinear data-enabled predictive control (DeePC) using kernel functions. Compared with existing methods that use kernels to parameterize multi-s…

eess.SY2024

Kernelized offset-free data-driven predictive control for nonlinear systems

Thomas Oliver de Jong, Mircea Lazar

This paper presents a kernelized offset-free data-driven predictive control scheme for nonlinear systems. Traditional model-based and data-driven predictive controllers often strug…

math.OC20242 cited

Koopman Data-Driven Predictive Control with Robust Stability and Recursive Feasibility Guarantees

Thomas de Jong, Valentina Breschi, Maarten Schoukens +1

In this paper, we consider the design of data-driven predictive controllers for nonlinear systems from input-output data via linear-in-control input Koopman lifted models. Instead…