scispace - formally typeset
P

Paul M.J. Van den Hof

Researcher at Eindhoven University of Technology

Publications -  198
Citations -  6037

Paul M.J. Van den Hof is an academic researcher from Eindhoven University of Technology. The author has contributed to research in topics: System identification & Identifiability. The author has an hindex of 34, co-authored 190 publications receiving 5543 citations. Previous affiliations of Paul M.J. Van den Hof include Delft University of Technology.

Papers
More filters
Journal ArticleDOI

Identification and control—closed-loop issues

TL;DR: An overview is given of some current research activities on the design of high-performance controllers for plants with uncertain dynamics, based on approximate identification and model-based control design, in dealing with the interplay between system identification and robust control design.
Journal ArticleDOI

Modelling and Identification with Rational Orthogonal Basis Functions

TL;DR: A recently developed general theory for basis construction will be presented, that is a generalization of the classical Laguerre theory, particularly exploiting the property that basis function models are linearly parametrized.
Journal ArticleDOI

System identification with generalized orthonormal basis functions

TL;DR: A least-squares identification method is studied that estimates a finite number of expansion coefficients in the series expansion of a transfer function, where the expansion is in terms of recently introduced generalized basis functions.
Journal ArticleDOI

Closed-Loop Issues in System Identification

TL;DR: The identification of dynamical systems on the basis of data, measured under closed-loop experimental conditions, is a problem which is highly relevant in many industrial applications as mentioned in this paper, and several procedures that have resulted from this research are reviewed and their characteristic properties compared.
Journal ArticleDOI

Robust Waterflooding Optimization of Multiple Geological Scenarios

TL;DR: In this paper, the authors presented an approach to reduce the impact of geological uncertainties in the field development phase known as robust optimization (RO), which uses a set of realizations that reflect the range of possible geological structures honoring the statistics of the geological uncertainties.