activity
20162024
most citedOn data-driven control: informativity of noisy input-output data with cross-covariance bounds

31 citations · 61 across the 9 of their papers we have counts for

collaborators

18 papers

eess.SY2024

Data-informativity conditions for structured linear systems with implications for dynamic networks

Paul M. J. Van den Hof, Shengling Shi, Stefanie J. M. Fonken +3

When estimating a single subsystem (module) in a linear dynamic network with a prediction error method, a data-informativity condition needs to be satisfied for arriving at a consi…

math.OC2022

On a Canonical Distributed Controller in the Behavioral Framework

Tom R. V. Steentjes, Mircea Lazar, Paul M. J. Van den Hof

Control in a classical transfer function or state-space setting typically views a controller as a signal processor: sensor outputs are mapped to actuator inputs. In behavioral syst…

eess.SY2022

Learning linear modules in a dynamic network with missing node observations

Karthik R. Ramaswamy, Giulio Bottegal, Paul M. J. Van den Hof

In order to identify a system (module) embedded in a dynamic network, one has to formulate a multiple-input estimation problem that necessitates certain nodes to be measured and in…

eess.SY2022★ 5 cited

Excitation allocation for generic identifiability of linear dynamic networks with fixed modules

H. J. Dreef, S. Shi, X. Cheng +2

Identifiability of linear dynamic networks requires the presence of a sufficient number of external excitation signals. The problem of allocating a minimal number of external signa…

math.OC2022★ 1 cited

Identifiability in Dynamic Acyclic Networks with Partial Excitations and Measurements

Xiaodong Cheng, Shengling Shi, Ioannis Lestas +1

This paper deals with dynamic networks in which the causality relations between the vertex signals are represented by linear time-invariant transfer functions (modules). Considerin…

math.OC2021★ 31 cited

On data-driven control: informativity of noisy input-output data with cross-covariance bounds

Tom R. V. Steentjes, Mircea Lazar, Paul M. J. Van den Hof

In this paper we develop new data informativity based controller synthesis methods that extend existing frameworks in two relevant directions: a more general noise characterization…