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- John C. Doyle

Discipline name
D-index
D-index (Discipline H-index) only includes papers and citation values for an examined
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Citations
Publications
World Ranking
National Ranking

Engineering and Technology
D-index
91
Citations
88,828
311
World Ranking
53
National Ranking
29

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

2004 - IEEE Control Systems Award “For fundamental contributions to theanalysis and control of uncertain systems.”

- Quantum mechanics
- Control theory
- Statistics

John C. Doyle focuses on Control theory, Robustness, Singular value, Mathematical optimization and Robust control. His research ties Norm and Control theory together. His work on Highly optimized tolerance as part of general Robustness study is frequently linked to Cellular basis, bridging the gap between disciplines.

His Singular value study incorporates themes from Uncertain systems, Computational complexity theory, Algorithm, Combinatorial complexity and Applied mathematics. His Mathematical optimization research includes elements of Focus, Matrix algebra, Linear matrix and Algebra. John C. Doyle studies Robust control, focusing on Linear fractional transformation in particular.

- State-space solutions to standard H/sub 2/ and H/sub infinity / control problems (4968 citations)
- The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. (2637 citations)
- Essentials of Robust Control (2521 citations)

John C. Doyle spends much of his time researching Control theory, Mathematical optimization, Robustness, Control theory and Robust control. His study in Optimal control, Control system, Linear system, Nonlinear system and Transfer function is carried out as part of his studies in Control theory. His Mathematical optimization study integrates concerns from other disciplines, such as Stability, Upper and lower bounds and Convex optimization.

The concepts of his Robustness study are interwoven with issues in Complex system, Computation, Parametric statistics and Bounded function. His Control theory research is multidisciplinary, relying on both Control and State. Robust control connects with themes related to Singular value in his study.

- Control theory (27.93%)
- Mathematical optimization (17.04%)
- Robustness (16.43%)

- Control theory (13.96%)
- Control theory (27.93%)
- Control (4.31%)

His primary scientific interests are in Control theory, Control theory, Control, Optimal control and Robustness. John C. Doyle combines subjects such as Scalability, Linear system, Stability, State and Key with his study of Control theory. In his research, John C. Doyle undertakes multidisciplinary study on Control theory and Negative feedback.

John C. Doyle interconnects Class and Control engineering in the investigation of issues within Control. His Optimal control research is under the purview of Mathematical optimization. His Linear-quadratic-Gaussian control study in the realm of Mathematical optimization connects with subjects such as Convexity and Intelligent transportation system.

- A System-Level Approach to Controller Synthesis (82 citations)
- System level synthesis (52 citations)
- Separable and Localized System-Level Synthesis for Large-Scale Systems (47 citations)

- Quantum mechanics
- Statistics
- Operating system

Control theory, Optimal control, Robustness, Control engineering and Scalability are his primary areas of study. John C. Doyle has researched Control theory in several fields, including Control system, Linear system, Network architecture and Topology. His studies deal with areas such as Key, Transparency and Robust control as well as Linear system.

His Optimal control research is multidisciplinary, incorporating elements of Actuator, Limit, Catalysis and Convex optimization. His research on Robustness concerns the broader Control theory. His Control engineering study also includes

- Class, which have a strong connection to Parametric statistics, Stability, Mechanism and Systems biology,
- Control which intersects with area such as Information theory.

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.

Robust and Optimal Control

J. Doyle.

**(1995)**

11233 Citations

State-space solutions to standard H/sub 2/ and H/sub infinity / control problems

J.C. Doyle;K. Glover;P.P. Khargonekar;B.A. Francis.

IEEE Transactions on Automatic Control **(1989)**

7727 Citations

Essentials of Robust Control

Kemin Zhou;John Comstock Doyle.

**(1997)**

4842 Citations

Feedback Control Theory

John Comstock Doyle;Bruce A. Francis;Allen R. Tannenbaum.

**(2009)**

4428 Citations

The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models.

M. Hucka;A. Finney;H. M. Sauro;H. Bolouri;H. Bolouri.

Bioinformatics **(2003)**

3338 Citations

Multivariable feedback design: Concepts for a classical/modern synthesis

J. Doyle;G. Stein.

IEEE Transactions on Automatic Control **(1981)**

3017 Citations

State-space solutions to standard H 2 and H ∞ control problems

John Doyle;Keith Glover;Pramod Khargonekar;Bruce Francis.

american control conference **(1988)**

2772 Citations

Analysis of feedback systems with structured uncertainties

John Doyle.

IEE Proceedings D Control Theory and Applications **(1982)**

2744 Citations

Fire in the Earth System

David M. J. S. Bowman;Jennifer K. Balch;Jennifer K. Balch;Jennifer K. Balch;Paulo Artaxo;William J. Bond.

Science **(2009)**

2098 Citations

State-space formulae for all stabilizing controllers that satisfy and H ∞ norm bound and relations to risk sensitivity

Keith Glover;John C. Doyle.

Systems & Control Letters **(1988)**

1975 Citations

California Institute of Technology

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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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