5 papers
Tube MPC for Bilinear Koopman Models using Robust Control Contraction Metrics
Thomas de Jong, Mircea Lazar
This paper presents a robust tube model predictive control (MPC) framework for nonlinear systems represented by bilinear Koopman models identified from data. We derive discrete-tim…
Mamba Sequence Modeling meets Model Predictive Control
Michiel Cevaal, Thomas de Jong, Mircea Lazar
In this paper, we consider the design of Model Predictive Control (MPC) algorithms based on Mamba neural networks. Mamba is a neural network architecture capable of sub-quadratic c…
Scalable Nonlinear DeePC: Bridging Direct and Indirect Methods and Basis Reduction
Thomas O. de Jong, Mircea Lazar, Siep Weiland +1
This paper studies regularized data-enabled predictive control (DeePC) within a nonlinear framework and its relationship to subspace predictive control (SPC). The -regularizati…
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…
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…