50 citations · 226 across the 23 of their papers we have counts for
24 papers
Co-designing a Layered Control Architecture
Chris Verhoek, Charis Stamouli, George J. Pappas +1
Layered control architectures (LCAs) are ubiquitous in complex engineering systems. However, in practice they are largely designed ad hoc and mostly dictated by the experience of t…
Model-Free Control for Residential Heating: Deployment and Simulation of Nonlinear Data-Enabled Predictive Control
Sebastian Zieglmeier, Chris Verhoek, Jaap Eising +1
Residential heating accounts for a large share of building energy use, and predictive control strategies can reduce it by anticipating rather than reacting to the room temperature…
A Continuous-Time Generalization of the LPV Fundamental Lemma
Philipp Schmitz, Chris Verhoek
Controller design for physical systems directly from data is of tremendous interest in both the industry and academia. However, the research on direct data-driven control has thus…
A subspace approach to data-driven predictive control for linear parameter-varying systems
Federico Porcari, Chris Verhoek, Valentina Breschi +2
This paper presents a subspace data-driven predictive control method for linear parameter-varying (LPV) systems. Starting from an affine LPV state-space model in innovation form, w…
A Quantitative Framework for Navigating Controller Design Tradeoffs under Computational Constraints
Chris Verhoek, Nikolai Matni
Computational constraints permeate the controller design process, and yet are rarely treated as explicit design constraints. Towards addressing this gap, we propose a quantitative…
Data-driven augmentation of first-principles models under constraint-free well-posedness and stability guarantees
Bendegúz Györök, Roel Drenth, Chris Verhoek +3
The integration of first-principles models with learning-based components, i.e., model augmentation, has gained increasing attention, as it offers higher model accuracy and faster…
Direct data-driven interpolation and approximation of linear parameter-varying system trajectories
Chris Verhoek, Ivan Markovsky, Roland Tóth
We consider the problem of estimating missing values in trajectories of linear parameter-varying (LPV) systems. We solve this interpolation problem for the class of shifted-affine…
A behavioral approach for LPV data-driven representations
Chris Verhoek, Ivan Markovsky, Sofie Haesaert +1
In this paper, we present a data-driven representation for linear parameter-varying (LPV) systems, which can be used for direct data-driven analysis and control of such systems. Sp…
Kernel-based multi-step predictors for data-driven analysis and control of nonlinear systems through the velocity form
Chris Verhoek, Roland Tóth
We propose kernel-based approaches for the construction of a single-step and multi-step predictor of the velocity form of nonlinear (NL) systems, which describes the time-differenc…
Learning-based model augmentation with LFRs
Jan H. Hoekstra, Chris Verhoek, Roland Tóth +1
Nonlinear system identification (NL-SI) has proven to be effective in obtaining accurate models for highly complex systems. In particular, recent encoder-based methods for artifici…
Decoupling parameter variation from noise: Biquadratic Lyapunov forms in data-driven LPV control
Chris Verhoek, Jaap Eising, Florian Dörfler +1
A promising step from linear towards nonlinear data-driven control is via the design of controllers for linear parameter-varying (LPV) systems, which are linear systems whose param…
A Linear Parameter-Varying Approach to Data Predictive Control
Chris Verhoek, Julian Berberich, Sofie Haesaert +2
By means of the linear parameter-varying (LPV) Fundamental Lemma, we derive novel data-driven predictive control (DPC) methods for LPV systems. In particular, we present output-fee…
Unified Behavioral Data-Driven Performance Analysis: A Generalized Plant Approach
L. M. Spin, C. Verhoek, W. P. M. H. Heemels +2
In this paper, we present a novel approach to combine data-driven non-parametric representations with model-based representations of dynamical systems. Based on a data-driven form…
Direct data-driven control with signal temporal logic specifications
Birgit C. van Huijgevoort, Chris Verhoek, Roland Tóth +1
Most control synthesis methods under temporal logic properties require a model of the system, however, identifying such a model can be a challenging task. In this work, we develop…
Learning Stable and Robust Linear Parameter-Varying State-Space Models
Chris Verhoek, Ruigang Wang, Roland Tóth
This paper presents two direct parameterizations of stable and robust linear parameter-varying state-space (LPV-SS) models. The model parametrizations guarantee a priori that for a…
Direct data-driven state-feedback control of general nonlinear systems
Chris Verhoek, Patrick J. W. Koelewijn, Sofie Haesaert +1
Through the use of the Fundamental Lemma for linear systems, a direct data-driven state-feedback control synthesis method is presented for a rather general class of nonlinear (NL)…
Data-driven Dissipativity Analysis of Linear Parameter-Varying Systems
Chris Verhoek, Julian Berberich, Sofie Haesaert +2
We derive direct data-driven dissipativity analysis methods for Linear Parameter-Varying (LPV) systems using a single sequence of input-scheduling-output data. By means of construc…
Direct data-driven LPV control of nonlinear systems: An experimental result
Chris Verhoek, Hossam S. Abbas, Roland Tóth
We demonstrate that direct data-driven control of nonlinear systems can be successfully accomplished via a behavioral approach that builds on a Linear Parameter-Varying (LPV) syste…
Direct Data-Driven State-Feedback Control of Linear Parameter-Varying Systems
Chris Verhoek, Roland Tóth, Hossam S. Abbas
The framework of linear parameter-varying (LPV) systems has shown to be a powerful tool for the design of controllers for complex nonlinear systems using linear tools. In this work…
LPV Modeling of the Atmospheric Flight Dynamics of a Generic Parafoil Return Vehicle
Matthis H. de Lange, Chris Verhoek, Valentin Preda +1
Obtaining models that can be used for control is of utmost importance to ensure the guidance and navigation of spacecraft, like a Generic Parafoil Return Vehicle (GPRV). In this pa…
Deep-Learning-Based Identification of LPV Models for Nonlinear Systems
Chris Verhoek, Gerben I. Beintema, Sofie Haesaert +2
The Linear Parameter-Varying (LPV) framework provides a modeling and control design toolchain to address nonlinear (NL) system behavior via linear surrogate models. Despite major r…
Fundamental Lemma for Data-Driven Analysis of Linear Parameter-Varying Systems
Chris Verhoek, Roland Tóth, Sofie Haesaert +1
Based on the Fundamental Lemma by Willems et al., the entire behaviour of a Linear Time-Invariant (LTI) system can be characterised by a single data sequence of the system as long…
Data-Driven Predictive Control for Linear Parameter-Varying Systems
Chris Verhoek, Hossam S. Abbas, Roland Tóth +1
Based on the extension of the behavioral theory and the Fundamental Lemma for Linear Parameter-Varying (LPV) systems, this paper introduces a Data-driven Predictive Control (DPC) s…
Convex Incremental Dissipativity Analysis of Nonlinear Systems - Extended version
Chris Verhoek, Patrick J. W. Koelewijn, Sofie Haesaert +1
Efficiently computable stability and performance analysis of nonlinear systems becomes increasingly more important in practical applications. Dissipativity can express stability an…