H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Electronics and Electrical Engineering H-index 30 Citations 6,011 179 World Ranking 3578 National Ranking 57

Research.com Recognitions

Awards & Achievements

2013 - IEEE Fellow For contributions to data-based controller design


What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Control theory
  • Mathematical analysis

Håkan Hjalmarsson focuses on Control theory, System identification, Control engineering, Mathematical optimization and Identification. His research combines Iterative method and Control theory. His studies deal with areas such as Estimation theory, Optimization problem, Algorithm, Applied mathematics and Nonlinear system as well as System identification.

His Algorithm research is multidisciplinary, relying on both Basis function, Fuzzy set, Estimator and Function approximation. His Control engineering research incorporates elements of Control and Control algorithm. Håkan Hjalmarsson interconnects Design of experiments, Covariance matrix and Noise in the investigation of issues within Mathematical optimization.

His most cited work include:

  • Nonlinear black-box modeling in system identification: a unified overview (1638 citations)
  • Iterative feedback tuning: theory and applications (711 citations)
  • From experiment design to closed-loop control (402 citations)

What are the main themes of his work throughout his whole career to date?

The scientist’s investigation covers issues in System identification, Control theory, Mathematical optimization, Algorithm and Identification. His System identification research incorporates themes from Linear system, Kernel, Impulse response, Covariance matrix and Applied mathematics. His Control theory study combines topics from a wide range of disciplines, such as Control engineering and Design of experiments.

His Control engineering study combines topics in areas such as Input design and Control. His research in Mathematical optimization intersects with topics in Convergence and Norm. His Algorithm research includes elements of Marginal likelihood and Bayes' theorem.

He most often published in these fields:

  • System identification (35.77%)
  • Control theory (35.51%)
  • Mathematical optimization (23.50%)

What were the highlights of his more recent work (between 2015-2021)?

  • Algorithm (21.15%)
  • System identification (35.77%)
  • Applied mathematics (20.63%)

In recent papers he was focusing on the following fields of study:

His scientific interests lie mostly in Algorithm, System identification, Applied mathematics, Identification and Mathematical optimization. When carried out as part of a general Algorithm research project, his work on Hyperparameter is frequently linked to work in Gaussian process, therefore connecting diverse disciplines of study. His biological study spans a wide range of topics, including Statistics, Linear system, Control theory and Delta method.

His Applied mathematics study integrates concerns from other disciplines, such as Parametric statistics, Parametric model, Estimator, Nonlinear system and Likelihood function. His Identification research also works with subjects such as

  • Function together with Parametrization and Gaussian noise,
  • Design of experiments, which have a strong connection to Interconnection, Spectrum and Control engineering. His study in Mathematical optimization is interdisciplinary in nature, drawing from both Kernel and Robustness.

Between 2015 and 2021, his most popular works were:

  • Robust EM kernel-based methods for linear system identification (31 citations)
  • Application-Oriented Input Design in System Identification: Optimal Input Design for Control [Applications of Control] (27 citations)
  • The Box-Jenkins Steiglitz-McBride algorithm (18 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Algorithm
  • Mathematical analysis

Håkan Hjalmarsson mainly investigates System identification, Mathematical optimization, Algorithm, Identification and Applied mathematics. His System identification study incorporates themes from Input design, Control theory, Real-time Control System, Control and Noise. His work in Control theory is not limited to one particular discipline; it also encompasses Model predictive control.

His Mathematical optimization research integrates issues from Marginal likelihood, Kernel and Linear dynamical system. Many of his research projects under Algorithm are closely connected to Gaussian process and Box–Jenkins with Gaussian process and Box–Jenkins, tying the diverse disciplines of science together. The study incorporates disciplines such as Design of experiments, Control theory and Interconnection in addition to Identification.

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.

Top Publications

Nonlinear black-box modeling in system identification: a unified overview

Jonas Sjöberg;Qinghua Zhang;Lennart Ljung;Albert Benveniste.
Automatica (1995)

2452 Citations

Iterative feedback tuning: theory and applications

H. Hjalmarsson;M. Gevers;S. Gunnarsson;O. Lequin.
IEEE Control Systems Magazine (1998)

925 Citations

From experiment design to closed-loop control

HåKan Hjalmarsson.
Automatica (2005)

516 Citations

Nonlinear black-box models in system identification: mathematical foundations

Anatoli Juditsky;Håkan Hjalmarsson;Albert Benveniste;Bernard Delyon.
Automatica (1995)

501 Citations

Iterative feedback tuning-an overview

Håkan Hjalmarsson.
International Journal of Adaptive Control and Signal Processing (2002)

470 Citations

A convergent iterative restricted complexity control design scheme

H. Hjalmarsson;S. Gunnarsson;M. Gevers.
conference on decision and control (1994)

385 Citations

For model-based control design, closed-loop identification gives better performance

Håkan Hjalmarsson;Michel Gevers;Franky De Bruyne.
Automatica (1996)

333 Citations

Input design via LMIs admitting frequency-wise model specifications in confidence regions

H. Jansson;H. Hjalmarsson.
IEEE Transactions on Automatic Control (2005)

229 Citations

Neural Networks in System Identification

Jonas Sjöberg;Håkan Hjalmarsson;Lennart Ljung.
IFAC Proceedings Volumes (1994)

201 Citations

System identification of complex and structured systems

Hakan Hjalmarsson.
european control conference (2009)

179 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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