D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Electronics and Electrical Engineering D-index 67 Citations 20,753 495 World Ranking 350 National Ranking 12

Research.com Recognitions

Awards & Achievements

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

2000 - IEEE Fellow For contributions to the theory of robust control system design.

Overview

What is he best known for?

The fields of study he is best known for:

  • Quantum mechanics
  • Control theory
  • Artificial intelligence

Ian R. Petersen mainly investigates Control theory, Robust control, Linear system, Mathematical optimization and Quadratic equation. His Control theory study frequently links to related topics such as Riccati equation. His studies in Robust control integrate themes in fields like Full state feedback, Position sensor and Variable structure control.

His research integrates issues of Nonlinear control, Nonlinear system, Transfer function, State and Quadratic growth in his study of Linear system. His Mathematical optimization research is multidisciplinary, incorporating elements of Kalman filter, Bounded function and Interval. His Linear-quadratic-Gaussian control research is multidisciplinary, relying on both Controllability and Linear-quadratic regulator.

His most cited work include:

  • Robust stabilization of uncertain linear systems: quadratic stabilizability and H/sup infinity / control theory (1324 citations)
  • A stabilization algorithm for a class of uncertain linear systems (1249 citations)
  • A Riccati equation approach to the stabilization of uncertain linear systems (732 citations)

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

Ian R. Petersen mostly deals with Control theory, Quantum, Robust control, Control theory and Quadratic equation. His Control theory research includes themes of Mathematical optimization and Minimax. Ian R. Petersen combines subjects such as Class and Riccati equation with his study of Mathematical optimization.

Norm is closely connected to Bounded function in his research, which is encompassed under the umbrella topic of Quadratic equation. His work in Linear-quadratic-Gaussian control tackles topics such as Linear-quadratic regulator which are related to areas like Algebraic Riccati equation. His Linear system research incorporates elements of Transfer function and State.

He most often published in these fields:

  • Control theory (57.71%)
  • Quantum (25.25%)
  • Robust control (19.07%)

What were the highlights of his more recent work (between 2016-2021)?

  • Quantum (25.25%)
  • Control theory (57.71%)
  • Quantum system (11.87%)

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

Ian R. Petersen focuses on Quantum, Control theory, Quantum system, Applied mathematics and Statistical physics. In his research, Quantum harmonic oscillator, Harmonic oscillator, Hamiltonian system and Optimal control is intimately related to Stochastic differential equation, which falls under the overarching field of Quantum. His work on Control theory deals in particular with Control theory, Control system, Nonlinear system, Transfer function and Robustness.

His Quantum system study combines topics from a wide range of disciplines, such as Quantum noise, Linear system, Controllability, Observer and Realization. As part of his studies on Linear system, he frequently links adjacent subjects like State. His Applied mathematics study also includes

  • Quantum state which intersects with area such as Gaussian,
  • Quadratic equation together with Bounded function,
  • Lyapunov function that intertwine with fields like Lyapunov stability.

Between 2016 and 2021, his most popular works were:

  • A Quantum Hamiltonian Identification Algorithm: Computational Complexity and Error Analysis (48 citations)
  • Rapid Lyapunov control of finite-dimensional quantum systems (41 citations)
  • Identifying Strong-Field Effects in Indirect Photofragmentation Reactions (40 citations)

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

  • Quantum mechanics
  • Control theory
  • Artificial intelligence

His scientific interests lie mostly in Quantum, Control theory, Quantum system, Applied mathematics and Statistical physics. Ian R. Petersen has researched Quantum in several fields, including Stochastic differential equation, Algorithm and Hamiltonian. His Control theory, Control system and Linear-quadratic-Gaussian control study in the realm of Control theory interacts with subjects such as Spiral.

His Linear-quadratic-Gaussian control study integrates concerns from other disciplines, such as Transfer function and Minimax. His research in Quantum system intersects with topics in Kalman filter and Hilbert space. Ian R. Petersen interconnects Reduced order, Lyapunov function, Nonlinear system, Class and Quantum state in the investigation of issues within Applied mathematics.

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.

Best Publications

Robust stabilization of uncertain linear systems: quadratic stabilizability and H/sup infinity / control theory

P.P. Khargonekar;I.R. Petersen;K. Zhou.
IEEE Transactions on Automatic Control (1990)

1967 Citations

A stabilization algorithm for a class of uncertain linear systems

I. R. Petersen.
Systems & Control Letters (1987)

1876 Citations

A Riccati equation approach to the stabilization of uncertain linear systems

I R Petersen;C V Hollot.
Automatica (1986)

1061 Citations

Optimal guaranteed cost control and filtering for uncertain linear systems

I.R. Petersen;D.C. McFarlane.
IEEE Transactions on Automatic Control (1994)

737 Citations

Robust Control Design Using H-∞ Methods

Ian Richard Petersen;Valery A. Ugrinovskii;Andrey V. Savkin.
(2012)

605 Citations

Disturbance attenuation and H^{∞} optimization: A design method based on the algebraic Riccati equation

I. Petersen.
IEEE Transactions on Automatic Control (1987)

509 Citations

Robust Kalman Filtering for Signals and Systems with Large Uncertainties

Ian R. Petersen;Andrey V. Savkin.
(1999)

493 Citations

Control of Linear Quantum Stochastic Systems

Matthew R. James;Hendra I. Nurdin;Ian R. Petersen.
Quantum-Atom Optics Downunder (2007), paper QME32 (2007)

493 Citations

Quantum control theory and applications: a survey

Daoyi Dong;Ian R. Petersen.
Iet Control Theory and Applications (2010)

460 Citations

Stability results for switched controller systems

Efstratios Skafidas;Robin J. Evans;Andrey V. Savkin;Ian R. Petersen.
Automatica (1999)

409 Citations

Best Scientists Citing Ian R. Petersen

Andrey V. Savkin

Andrey V. Savkin

UNSW Sydney

Publications: 132

Peng Shi

Peng Shi

University of Adelaide

Publications: 80

Zidong Wang

Zidong Wang

Brunel University London

Publications: 72

Matthew R. James

Matthew R. James

Australian National University

Publications: 66

S. O. Reza Moheimani

S. O. Reza Moheimani

The University of Texas at Dallas

Publications: 59

Jinhua She

Jinhua She

Tokyo University of Technology

Publications: 57

Lihua Xie

Lihua Xie

Nanyang Technological University

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Dennis S. Bernstein

Dennis S. Bernstein

University of Michigan–Ann Arbor

Publications: 54

James Lam

James Lam

University of Hong Kong

Publications: 50

Min Wu

Min Wu

China University of Geosciences

Publications: 49

Qingling Zhang

Qingling Zhang

Yale University

Publications: 46

Wassim M. Haddad

Wassim M. Haddad

Georgia Institute of Technology

Publications: 45

Uri Shaked

Uri Shaked

Tel Aviv University

Publications: 44

Guang-Hong Yang

Guang-Hong Yang

Northeastern University

Publications: 42

Daoyi Dong

Daoyi Dong

UNSW Sydney

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Shengyuan Xu

Shengyuan Xu

Nanjing University of Science and Technology

Publications: 42

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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