5 citations · 11 across the 12 of their papers we have counts for
17 papers
Experiment design using prior knowledge on controllability and stabilizability
Amir Shakouri, Henk J. van Waarde, M. Kanat Camlibel
In this paper, we consider the problem of designing input signals for an unknown linear time-invariant system in such a way that the resulting input-state data is suitable for iden…
Data-Driven Stabilization Using Prior Knowledge on Stabilizability and Controllability
Amir Shakouri, Henk J. van Waarde, Tren M. J. T. Baltussen +1
In this work, we study data-driven stabilization of linear time-invariant systems using prior knowledge of system-theoretic properties, specifically stabilizability and controllabi…
Learning in Memristive Neural Networks
H. M. Heidema, H. J. van Waarde, B. Besselink
Memristors are nonlinear two-terminal circuit elements whose resistance at a given time depends on past electrical stimuli. Recently, networks of memristors have received attention…
Data-driven stabilization of polynomial systems using density functions
Huayuan Huang, M. Kanat Camlibel, Raffaella Carloni +1
This paper studies data-driven stabilization of a class of unknown polynomial systems using data corrupted by bounded noise. Existing work addressing this problem has focused on de…
Bridging Model Reference Adaptive Control and Data Informativity
Jiwei Wang, Simone Baldi, Henk J. van Waarde
The goal of model reference adaptive control (MRAC) is to ensure that the trajectories of an unknown dynamical system track those of a given reference model. This is done by means…
Synthesis of Dissipative Systems Using Input-State Data
Encho T. Nguyen, Henk J. van Waarde
This paper deals with the data-driven synthesis of dissipative linear systems in discrete time. We collect finitely many noisy data samples with which we synthesise a controller th…
Learning in memristive electrical circuits
Marieke Heidema, Henk van Waarde, Bart Besselink
Memristors are nonlinear two-terminal circuit elements whose resistance at a given time depends on past electrical stimuli. Recently, networks of memristors have received attention…
Robust Fundamental Lemma for Data-driven Control
Jeremy Coulson, Henk van Waarde, Florian Dörfler
The fundamental lemma by Willems and coauthors facilitates a parameterization of all trajectories of a linear time-invariant system in terms of a single, measured one. This result…
Behavioral uncertainty quantification for data-driven control
Alberto Padoan, Jeremy Coulson, Henk J. van Waarde +2
This paper explores the problem of uncertainty quantification in the behavioral setting for data-driven control. Building on classical ideas from robust control, the problem is reg…
A Matrix Finsler's Lemma with Applications to Data-Driven Control
Henk J. van Waarde, M. Kanat Camlibel
In a recent paper it was shown how a matrix S-lemma can be applied to construct controllers from noisy data. The current paper complements these results by proving a matrix version…
Data-driven output synchronization of heterogeneous leader-follower multi-agent systems
Junjie Jiao, Henk J. van Waarde, Harry L. Trentelman +2
This paper deals with data-driven output synchronization for heterogeneous leader-follower linear multi-agent systems. Given a multi-agent system that consists of one autonomous le…
Beyond Persistent Excitation: Online Experiment Design for Data-Driven Modeling and Control
Henk J. van Waarde
This paper presents a new experiment design method for data-driven modeling and control. The idea is to select inputs online (using past input/output data), leading to desirable ra…
On Controllability and Persistency of Excitation in Data-Driven Control: Extensions of Willems' Fundamental Lemma
Yue Yu, Shahriar Talebi, Henk J. van Waarde +3
Willems' fundamental lemma asserts that all trajectories of a linear time-invariant system can be obtained from a finite number of measured ones, assuming that controllability and…
Properties of pattern matrices with applications to structured systems
B. M. Shali, H. J. van Waarde, M. K. Camlibel +1
The exact parameter values of mathematical models are often uncertain or even unknown. Nevertheless, we may have access to crude information about the parameters, e.g., that some o…
From noisy data to feedback controllers: non-conservative design via a matrix S-lemma
Henk J. van Waarde, M. Kanat Camlibel, Mehran Mesbahi
We propose a new method to obtain feedback controllers of an unknown dynamical system directly from noisy input/state data. The key ingredient of our design is a new matrix S-lemma…
Data-driven parameterizations of suboptimal LQR and H2 controllers
Henk J. van Waarde, Mehran Mesbahi
In this paper we design suboptimal control laws for an unknown linear system on the basis of measured data. We focus on the suboptimal linear quadratic regulator problem and the su…
Topology Identification of Heterogeneous Networks: Identifiability and Reconstruction
Henk J. van Waarde, Pietro Tesi, M. Kanat Camlibel
This paper addresses the problem of identifying the graph structure of a dynamical network using measured input/output data. This problem is known as topology identification and ha…