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- Michel Verhaegen

Discipline name
H-index
Citations
Publications
World Ranking
National Ranking

Electronics and Electrical Engineering
H-index
45
Citations
11,271
240
World Ranking
1455
National Ranking
13

2011 - Fellow of the International Federation of Automatic Control (IFAC)

- Statistics
- Control theory
- Artificial intelligence

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.

- Identification of the deterministic part of MIMO state space models given in innovations form from input-output data (792 citations)
- Subspace model identification Part 1. The output-error state-space model identification class of algorithms (588 citations)
- Filtering and System Identification: A Least Squares Approach (404 citations)

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.

- Control theory (36.52%)
- Algorithm (21.48%)
- Optics (18.36%)

- Optics (18.36%)
- Algorithm (21.48%)
- Adaptive optics (14.45%)

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

- Artificial intelligence which intersects with area such as Pattern recognition,
- Spline that intertwine with fields like Nonlinear system.

- Subspace identification of individual systems in a large-scale heterogeneous network (41 citations)
- Constrained Subspace Method for the Identification of Structured State-Space Models (COSMOS) (32 citations)
- Identification of structured state-space models (26 citations)

- Statistics
- Optics
- Artificial intelligence

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)**

1138 Citations

Subspace model identification Part 2. Analysis of the elementary output-error state-space model identification algorithm

Michel Verhaegen.

International Journal of Control **(1992)**

1008 Citations

Subspace model identification Part 1. The output-error state-space model identification class of algorithms

Michel Verhaegen;Patrick Dewilde.

International Journal of Control **(1992)**

920 Citations

Filtering and System Identification: A Least Squares Approach

Michel Verhaegen;Vincent Verdult.

**(2007)**

866 Citations

Identifying MIMO Wiener systems using subspace model identification methods

David Westwick;Michel Verhaegen.

Signal Processing **(1996)**

339 Citations

Distributed Control for Identical Dynamically Coupled Systems: A Decomposition Approach

P. Massioni;M. Verhaegen.

IEEE Transactions on Automatic Control **(2009)**

319 Citations

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)**

305 Citations

Subspace algorithms for the identification of multivarible dynamic errors-in-variables models

C. T. Chou;Michel Verhaegen.

Automatica **(1997)**

287 Citations

Numerical aspects of different Kalman filter implementations

M. Verhaegen;P. Van Dooren.

IEEE Transactions on Automatic Control **(1986)**

285 Citations

Recursive subspace identification of linear and non-linear Wiener state-space models

Marco Lovera;Tony Gustafsson;Michel Verhaegen.

Automatica **(2000)**

256 Citations

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.

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