2011 - Fellow of the International Federation of Automatic Control (IFAC)
Michel Verhaegen mainly investigates Control theory, System identification, Subspace topology, Algorithm and Control theory. Specifically, his work in Control theory is concerned with the study of Nonlinear system. Michel Verhaegen has researched System identification in several fields, including Linear model, Multivariable calculus, Frequency response, MIMO and Mathematical optimization.
His Subspace topology research is multidisciplinary, incorporating elements of Bilinear interpolation, Affine transformation, Identification, Kernel method and Observability. His Algorithm study incorporates themes from Linear system, Linear subspace, State space, State-space representation and White noise. The various areas that Michel Verhaegen examines in his Control theory study include Optimal control, Stability, Linear matrix inequality, Fault tolerance and Fault.
Michel Verhaegen mainly investigates Control theory, Algorithm, Optics, Subspace topology and Mathematical optimization. His biological study spans a wide range of topics, including Control engineering and System identification. His Algorithm research includes elements of Matrix, Multivariable calculus, State-space representation, Phase retrieval and Kalman filter.
His research in Subspace topology tackles topics such as Identification which are related to areas like State space. His work carried out in the field of Mathematical optimization brings together such families of science as Computational complexity theory, Applied mathematics and Convex optimization. The Wavefront study which covers Artificial intelligence that intersects with Pattern recognition.
Michel Verhaegen mostly deals with Optics, Algorithm, Adaptive optics, Phase retrieval and Wavefront. His study in Algorithm is interdisciplinary in nature, drawing from both Subspace topology, Matrix, Rank and Identification. Michel Verhaegen has included themes like Structure, Dynamical systems theory, Matrix decomposition, Markov chain and Realization in his Subspace topology study.
His Markov chain study combines topics in areas such as Markov process, Control theory, Filter, Filter design and Fault. The study incorporates disciplines such as Optimization problem and Linear system in addition to Identification. His Wavefront research also works with subjects such as
Algorithm, Optics, Subspace topology, Identification and Control theory are his primary areas of study. His Algorithm research incorporates elements of Gerchberg–Saxton algorithm, Nonlinear system, Regression and Rank. His work in Regression tackles topics such as Kriging which are related to areas like System identification.
His Subspace topology research incorporates themes from Structure, Tensor, Parametrization, Markov chain and Realization. In general Identification, his work in Parameter identification problem is often linked to Heterogeneous network linking many areas of study. Michel Verhaegen integrates several fields in his works, including Control theory and Inverse.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Identification of the deterministic part of MIMO state space models given in innovations form from input-output data
Michel Verhaegen.
Automatica (1994)
Subspace model identification Part 2. Analysis of the elementary output-error state-space model identification algorithm
Michel Verhaegen.
International Journal of Control (1992)
Subspace model identification Part 1. The output-error state-space model identification class of algorithms
Michel Verhaegen;Patrick Dewilde.
International Journal of Control (1992)
Filtering and System Identification: A Least Squares Approach
Michel Verhaegen;Vincent Verdult.
(2007)
Identifying MIMO Wiener systems using subspace model identification methods
David Westwick;Michel Verhaegen.
Signal Processing (1996)
Distributed Control for Identical Dynamically Coupled Systems: A Decomposition Approach
P. Massioni;M. Verhaegen.
IEEE Transactions on Automatic Control (2009)
Development of advanced driver assistance systems with vehicle hardware-in-the-loop simulations
OJ Gietelink;J Jeroen Ploeg;de B Bart Schutter;MH Verhaegen.
Vehicle System Dynamics (2006)
Subspace algorithms for the identification of multivarible dynamic errors-in-variables models
C. T. Chou;Michel Verhaegen.
Automatica (1997)
Numerical aspects of different Kalman filter implementations
M. Verhaegen;P. Van Dooren.
IEEE Transactions on Automatic Control (1986)
Recursive subspace identification of linear and non-linear Wiener state-space models
Marco Lovera;Tony Gustafsson;Michel Verhaegen.
Automatica (2000)
Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.
If you think any of the details on this page are incorrect, let us know.
UNSW Sydney
Lund University
Eindhoven University of Technology
TU Wien
Uppsala University
Linköping University
Delft University of Technology
University of California, Berkeley
Linköping University
Université Catholique de Louvain
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: