World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
49
Citations
14610
World Ranking
2884
National Ranking
93

Peter J. Gawthrop publication distribution in Electronics and Electrical Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Peter J. Gawthrop sits on this spectrum.

34–53 publications: 24 scientists 54–73 publications: 52 scientists 74–93 publications: 114 scientists 94–113 publications: 203 scientists 114–133 publications: 269 scientists 134–153 publications: 355 scientists 154–173 publications: 403 scientists 174–193 publications: 445 scientists 194–213 publications: 430 scientists 214–233 publications: 431 scientists 234–253 publications: 399 scientists 254–273 publications: 366 scientists 274–293 publications: 335 scientists 294–313 publications: 300 scientists 314–333 publications: 276 scientists 334–353 publications: 250 scientists 354–373 publications: 214 scientists 374–393 publications: 187 scientists 394–413 publications: 152 scientists 414–433 publications: 169 scientists 434–453 publications: 147 scientists 454–473 publications: 111 scientists 474–493 publications: 117 scientists 494–513 publications: 103 scientists 514–533 publications: 99 scientists 534–553 publications: 92 scientists 554–573 publications: 75 scientists 574–593 publications: 58 scientists 594–613 publications: 69 scientists 614–633 publications: 50 scientists 634–653 publications: 62 scientists 654–673 publications: 54 scientists 674–693 publications: 44 scientists 694–713 publications: 37 scientists 714–733 publications: 28 scientists 734–753 publications: 26 scientists 754–773 publications: 26 scientists 774–793 publications: 19 scientists 794–813 publications: 23 scientists 814–833 publications: 20 scientists 834–853 publications: 16 scientists 854–873 publications: 20 scientists 874–893 publications: 11 scientists 894–913 publications: 11 scientists 914–933 publications: 16 scientists 934–953 publications: 13 scientists 954–973 publications: 10 scientists 974–993 publications: 11 scientists 994–1,013 publications: 9 scientists 1,014–1,033 publications: 9 scientists 1,034–1,053 publications: 10 scientists 1,054–1,064 publications: 6 scientists 1,065+ publications: 99 scientists
34 publications 1,065+

This scientist: 211 publications — 33rd percentile

33% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,065 publications or more.

Peter J. Gawthrop D-index placement in Electronics and Electrical Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Electronics and Electrical Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Peter J. Gawthrop sits on this spectrum.

30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 262 scientists 34 D-Index: 244 scientists 35 D-Index: 236 scientists 36 D-Index: 211 scientists 37 D-Index: 220 scientists 38 D-Index: 214 scientists 39 D-Index: 214 scientists 40 D-Index: 205 scientists 41 D-Index: 187 scientists 42 D-Index: 194 scientists 43 D-Index: 201 scientists 44 D-Index: 155 scientists 45 D-Index: 189 scientists 46 D-Index: 148 scientists 47 D-Index: 160 scientists 48 D-Index: 134 scientists 49 D-Index: 130 scientists 50 D-Index: 141 scientists 51 D-Index: 156 scientists 52 D-Index: 108 scientists 53 D-Index: 130 scientists 54 D-Index: 112 scientists 55 D-Index: 97 scientists 56 D-Index: 111 scientists 57 D-Index: 102 scientists 58 D-Index: 108 scientists 59 D-Index: 120 scientists 60 D-Index: 103 scientists 61 D-Index: 93 scientists 62 D-Index: 92 scientists 63 D-Index: 74 scientists 64 D-Index: 77 scientists 65 D-Index: 73 scientists 66 D-Index: 64 scientists 67 D-Index: 69 scientists 68 D-Index: 60 scientists 69 D-Index: 39 scientists 70 D-Index: 57 scientists 71 D-Index: 59 scientists 72 D-Index: 46 scientists 73 D-Index: 49 scientists 74 D-Index: 38 scientists 75 D-Index: 35 scientists 76 D-Index: 32 scientists 77 D-Index: 35 scientists 78 D-Index: 31 scientists 79 D-Index: 22 scientists 80 D-Index: 34 scientists 81 D-Index: 31 scientists 82 D-Index: 34 scientists 83 D-Index: 23 scientists 84 D-Index: 18 scientists 85 D-Index: 30 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 20 scientists 89 D-Index: 8 scientists 90 D-Index: 17 scientists 91 D-Index: 7 scientists 92 D-Index: 14 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 12 scientists 97 D-Index: 10 scientists 98 D-Index: 10 scientists 99 D-Index: 12 scientists 100 D-Index: 16 scientists 101 D-Index: 5 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 8 scientists 105 D-Index: 9 scientists 106 D-Index: 13 scientists 107 D-Index: 4 scientists 108 D-Index: 5 scientists 109 D-Index: 10 scientists 110 D-Index: 8 scientists 111+ D-Index: 96 scientists
30 D-Index 111+

This scientist: 49 D-Index — 58th percentile

58% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 111 D-Index or more.

Overview

What is he best known for?

The fields of study he is best known for:

  • Control theory
  • Artificial intelligence
  • Programming language

His primary scientific interests are in Control theory, Control engineering, Nonlinear system, Control theory and Model predictive control. Self-tuning, Adaptive control, Intermittent control, Inverted pendulum and Compensation are the subjects of his Control theory studies. Peter J. Gawthrop combines subjects such as Control system and Basis function with his study of Control engineering.

The Nonlinear system study which covers Linear system that intersects with Observer, Torque, State space and Multivariable calculus. As a member of one scientific family, Peter J. Gawthrop mostly works in the field of Control theory, focusing on Stability and, on occasion, Range and Automatic control. Peter J. Gawthrop interconnects Nonlinear control and Optimal control in the investigation of issues within Model predictive control.

His most cited work include:

  • Neural networks for control systems: a survey (1614 citations)
  • A nonlinear disturbance observer for robotic manipulators (980 citations)
  • Self-tuning controller (761 citations)

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

Peter J. Gawthrop mainly focuses on Control theory, Control engineering, Bond graph, Model predictive control and Control theory. His Control theory study is mostly concerned with Nonlinear system, Intermittent control, Control system, Adaptive control and Self-tuning. His Nonlinear system study combines topics from a wide range of disciplines, such as Linear system and Mathematical optimization.

The Adaptive control study combines topics in areas such as Weighting and Robust control. His Control engineering research is multidisciplinary, incorporating elements of Control, Process control and Identification. His Model predictive control research integrates issues from Full state feedback, Mechanical system, Quadratic programming and Optimal control.

He most often published in these fields:

  • Control theory (53.98%)
  • Control engineering (32.74%)
  • Bond graph (28.32%)

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

  • Bond graph (28.32%)
  • Energy based (5.31%)
  • Biological system (4.87%)

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

His main research concerns Bond graph, Energy based, Biological system, Systems biology and Mathematical model. His research integrates issues of Statistical physics, Living systems and Transduction in his study of Bond graph. His work in Energy based covers topics such as Feedback control which are related to areas like Control system, Transfer function, Control engineering, Energy feedback and Class.

His study in Control system is interdisciplinary in nature, drawing from both Feedback loop and Linear control. Energy feedback is often connected to Control theory in his work. His work carried out in the field of Systems biology brings together such families of science as Structure, Modularity and Correctness.

Between 2015 and 2021, his most popular works were:

  • Modular bond-graph modelling and analysis of biomolecular systems. (27 citations)
  • Bond Graph Modeling of Chemiosmotic Biomolecular Energy Transduction (22 citations)
  • Bond Graph Modelling of Chemiosmotic Biomolecular Energy Transduction (14 citations)

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

  • Control theory
  • Artificial intelligence
  • Programming language

His primary areas of study are Bond graph, Energy based, Biological system, Systems biology and Electron transport chain. His studies in Bond graph integrate themes in fields like Range and Robustness. His research on Energy based frequently connects to adjacent areas such as Transduction.

His Biophysics research extends to the thematically linked field of Systems biology. Peter J. Gawthrop combines Electron transport chain and Chemiosmosis in his studies. His Mathematical model research incorporates elements of Scale, Conservation law, Charge conservation, Physical system and Statistical physics.

Best Publications

  • Neural networks for control systems: a survey

    K. J. Hunt;D. Sbarbaro;R. Żbikowski;P. J. Gawthrop

  • A nonlinear disturbance observer for robotic manipulators

    Wen-Hua Chen;D.J. Ballance;P.J. Gawthrop;J. O'Reilly

  • Self-tuning controller

    D.W. Clarke;P.J. Gawthrop

  • Self-tuning control

    D.W. Clarke;P.J. Gawthrop

  • Brief Optimal control of nonlinear systems: a predictive control approach

    Wen-Hua Chen;Donald J. Ballance;Peter J Gawthrop

  • Metamodelling: for bond graphs and dynamic systems

    Peter Gawthrop;Lorcan Smith

  • Bond-graph modeling

    P.J. Gawthrop;G.P. Bevan

  • Human control of an inverted pendulum: Is continuous control necessary? Is intermittent control effective? Is intermittent control physiological?

    Ian D. Loram;Henrik Gollee;Martin Lakie;Peter J. Gawthrop

  • Intermittent control: a computational theory of human control

    Peter Gawthrop;Ian Loram;Martin Lakie;Henrik Gollee

  • Continuous-time generalized predictive control (CGPC)

    H. Demircioğlu;P. J. Gawthrop

  • Self-tuning PID controllers: Algorithms and implementation

    P. Gawthrop

  • Nonlinear PID predictive controller

    Wen-Hua Chen;Donald J. Ballance;Peter J. Gawthrop;Jenny J. Gribble

  • Some interpretations of the self-tuning controller

    P.J. Gawthrop

  • Continuous-time self-tuning control

    P. J. Gawthrop

  • Implementation and application of microprocessor-based self-tuners

    D. W. Clarke;P. J. Gawthrop

  • The frequency of human, manual adjustments in balancing an inverted pendulum is constrained by intrinsic physiological factors

    Ian David Loram;Peter Gawthrop;Martin Lakie

  • Identification of time delays using a polynomial identification method

    P.J. Gawthrop;M.T. Nihtilä

  • Off-equilibrium linearisation and design of gain-scheduled control with application to vehicle speed control

    T.A. Johansen;K.J. Hunt;P.J. Gawthrop;H. Fritz

  • Event-driven intermittent control

    Peter J. Gawthrop;Liuping Wang

  • CONTINUOUS-TIME GENERALIZED PREDICTIVE CONTROL (CGPC)

    P.J. Gawthrop;H. Demircioğlu

  • Control of Time-Delay Systems

    P.J. Gawthrop

Frequent Co-Authors

Liuping Wang
Liuping Wang RMIT University
Edmund J. Crampin
Edmund J. Crampin University of Melbourne
Simon A Neild
Simon A Neild University of Bristol
David J. Wagg
David J. Wagg University of Sheffield
Wen-Hua Chen
Wen-Hua Chen Loughborough University
Peter C. Young
Peter C. Young Lancaster University
Tor Arne Johansen
Tor Arne Johansen Norwegian University of Science and Technology
David H. Owens
David H. Owens University of Sheffield
Kay Chen Tan
Kay Chen Tan Hong Kong Polytechnic University
Eric Rogers
Eric Rogers University of Southampton

If you think any of the details on this page are incorrect, let us know.

Report an issue

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:

Related Online Degrees & Career Pathways

For those interested in Electronics and Electrical Engineering, exploring flexible learning options can be crucial. Many students balance work and study by enrolling in accelerated online degree programs for working adults, which offer an efficient way to earn degrees without compromising professional commitments.

Additionally, competency-based learning is gaining popularity, allowing students to progress at their own pace by demonstrating mastery of skills. This approach is well-represented through competency based masters degree options that cater to specific career goals in engineering and related fields.

For those interested in merging technical expertise with education, the best online teaching master's programs provide pathways to become educators or trainers in engineering disciplines.

It's also important to highlight accessible opportunities for military families. Numerous online colleges for military spouses offer tailored support and flexible scheduling, making it easier to pursue advanced degrees without relocation or disruption.

Best Scientists Citing Peter J. Gawthrop

Trending Scientists

Recently Published Articles