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David Q. Mayne

D-Index & Metrics

Discipline name D-Index World Ranking National Ranking Publications Citations
Electronics and Electrical Engineering 64 1251 58 225 36265

David Q. Mayne publications per year

The chart shows the history of publications by David Q. Mayne between 1959 and 2021, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. David Q. Mayne published across 63 years, from 1959 to 2021, averaging 3.8 papers a year. Output peaked at 12 publications in 1982. 2 of the 239 publications appeared in the last two years.

No. of publications
5 10
Bar chart. Horizontal axis: year, 1959 to 2021. Vertical axis: number of publications, 0 to 12. Peak 12 publications in 1982. 1959: 1 publication 1960: 1 publication 1961: 0 publications 1962: 0 publications 1963: 2 publications 1964: 2 publications 1965: 1 publication 1966: 5 publications 1967: 2 publications 1968: 1 publication 1969: 4 publications 1970: 3 publications 1971: 2 publications 1972: 4 publications 1973: 9 publications 1974: 2 publications 1975: 2 publications 1976: 3 publications 1977: 3 publications 1978: 1 publication 1979: 9 publications 1980: 5 publications 1981: 5 publications 1982: 12 publications 1983: 3 publications 1984: 9 publications 1985: 4 publications 1986: 3 publications 1987: 4 publications 1988: 6 publications 1989: 3 publications 1990: 5 publications 1991: 9 publications 1992: 6 publications 1993: 4 publications 1994: 5 publications 1995: 8 publications 1996: 2 publications 1997: 4 publications 1998: 2 publications 1999: 4 publications 2000: 3 publications 2001: 4 publications 2002: 6 publications 2003: 6 publications 2004: 6 publications 2005: 11 publications 2006: 5 publications 2007: 6 publications 2008: 1 publication 2009: 3 publications 2010: 5 publications 2011: 6 publications 2012: 1 publication 2013: 4 publications 2014: 3 publications 2015: 3 publications 2016: 2 publications 2017: 0 publications 2018: 1 publication 2019: 1 publication 2020: 1 publication 2021: 1 publication
1959 2021

239 publications in total across all disciplines

View publications per year as a table
David Q. Mayne: publications per year, 1959 to 2021
Year Publications
1959 1
1960 1
1961 0
1962 0
1963 2
1964 2
1965 1
1966 5
1967 2
1968 1
1969 4
1970 3
1971 2
1972 4
1973 9
1974 2
1975 2
1976 3
1977 3
1978 1
1979 9
1980 5
1981 5
1982 12
1983 3
1984 9
1985 4
1986 3
1987 4
1988 6
1989 3
1990 5
1991 9
1992 6
1993 4
1994 5
1995 8
1996 2
1997 4
1998 2
1999 4
2000 3
2001 4
2002 6
2003 6
2004 6
2005 11
2006 5
2007 6
2008 1
2009 3
2010 5
2011 6
2012 1
2013 4
2014 3
2015 3
2016 2
2017 0
2018 1
2019 1
2020 1
2021 1
Total 239
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David Q. Mayne 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 David Q. Mayne sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 53 bars. Horizontal axis: publications, 34–53 to 1,065+. Vertical axis: number of scientists, 0 to 445. Most scientists, 445, have 174–193 publications. The last bar groups every scientist with 1,065 publications or more. The highlighted bar, 214–233 publications, is where this scientist sits. 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
34–53 publications 1,065+

This scientist: 225 publications — 38th percentile

38% of scientists in this discipline score the same or lower.

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

View publications distribution as a table
Number of Electronics and Electrical Engineering scientists by publication count, Research.com 2026 ranking edition. Based on 6,875 ranked scientists.
Publications Scientists This scientist
34–53 24
54–73 52
74–93 114
94–113 203
114–133 269
134–153 355
154–173 403
174–193 445
194–213 430
214–233 431 225
234–253 399
254–273 366
274–293 335
294–313 300
314–333 276
334–353 250
354–373 214
374–393 187
394–413 152
414–433 169
434–453 147
454–473 111
474–493 117
494–513 103
514–533 99
534–553 92
554–573 75
574–593 58
594–613 69
614–633 50
634–653 62
654–673 54
674–693 44
694–713 37
714–733 28
734–753 26
754–773 26
774–793 19
794–813 23
814–833 20
834–853 16
854–873 20
874–893 11
894–913 11
914–933 16
934–953 13
954–973 10
974–993 11
994–1,013 9
1,014–1,033 9
1,034–1,053 10
1,054–1,064 6
1,065+ 99
Download as CSV

David Q. Mayne 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 David Q. Mayne sits on this spectrum.

No. of scientists
50 100 150 200 250
Bar chart with 82 bars. Horizontal axis: D-Index, 30 to 111+. Vertical axis: number of scientists, 0 to 263. Most scientists, 263, have 32 D-Index. The last bar groups every scientist with 111 D-Index or more. The highlighted bar, 64 D-Index, is where this scientist sits. 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: 64 D-Index — 82nd percentile

82% of scientists in this discipline score the same or lower.

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

View D-Index distribution as a table
Number of Electronics and Electrical Engineering scientists by D-index, Research.com 2026 ranking edition. Based on 6,875 ranked scientists.
D-Index Scientists This scientist
30 178
31 257
32 263
33 262
34 244
35 236
36 211
37 220
38 214
39 214
40 205
41 187
42 194
43 201
44 155
45 189
46 148
47 160
48 134
49 130
50 141
51 156
52 108
53 130
54 112
55 97
56 111
57 102
58 108
59 120
60 103
61 93
62 92
63 74
64 77 64
65 73
66 64
67 69
68 60
69 39
70 57
71 59
72 46
73 49
74 38
75 35
76 32
77 35
78 31
79 22
80 34
81 31
82 34
83 23
84 18
85 30
86 19
87 19
88 20
89 8
90 17
91 7
92 14
93 9
94 15
95 10
96 12
97 10
98 10
99 12
100 16
101 5
102 7
103 7
104 8
105 9
106 13
107 4
108 5
109 10
110 8
111+ 96
Download as CSV

Research.com Recognitions

  • 2009 - IEEE Control Systems Award “For contributions to the application of optimization to modern control theory.”
  • 2006 - Fellow of the International Federation of Automatic Control (IFAC)
  • 1985 - Fellow of the Royal Society, United Kingdom
  • 1981 - IEEE Fellow For contributions to optimal control and dynamic programming.

Overview

What is he best known for?

The fields of study he is best known for:

  • Control theory
  • Mathematical analysis
  • Statistics

David Q. Mayne mainly focuses on Control theory, Mathematical optimization, Optimal control, Linear system and Model predictive control. His Control theory study which covers Estimator that intersects with State observer, Set and Adaptive algorithm. His work in Mathematical optimization addresses subjects such as Stability, which are connected to disciplines such as Constraint.

His studies in Optimal control integrate themes in fields like Kalman filter, Piecewise linear function and Nonlinear system. His study in Model predictive control is interdisciplinary in nature, drawing from both Control engineering, Systems engineering, Exponential stability and Robustness. His Nonlinear control research focuses on subjects like Linear-quadratic-Gaussian control, which are linked to Automatic control.

His most cited work include:

  • Survey Constrained model predictive control: Stability and optimality (6379 citations)
  • Robust receding horizon control of constrained nonlinear systems (955 citations)
  • Robust model predictive control of constrained linear systems with bounded disturbances (893 citations)

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

David Q. Mayne spends much of his time researching Control theory, Mathematical optimization, Optimal control, Linear system and Nonlinear system. His studies link Model predictive control with Control theory. His study looks at the intersection of Model predictive control and topics like Stability with Constraint.

His Mathematical optimization research is multidisciplinary, relying on both Function and Algorithm, Theory of computation. David Q. Mayne has researched Optimal control in several fields, including State, Piecewise linear function, Discrete time and continuous time and Bellman equation. The Nonlinear system study combines topics in areas such as Interval and Finite set.

He most often published in these fields:

  • Control theory (47.71%)
  • Mathematical optimization (45.41%)
  • Optimal control (31.65%)

What were the highlights of his more recent work (between 2001-2021)?

  • Control theory (47.71%)
  • Model predictive control (20.18%)
  • Mathematical optimization (45.41%)

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

David Q. Mayne mainly investigates Control theory, Model predictive control, Mathematical optimization, Optimal control and Robust control. His Control theory study frequently draws connections between related disciplines such as Bounded function. His Mathematical optimization study combines topics in areas such as Function, Piecewise linear function, Parametric programming and Piecewise.

The concepts of his Optimal control study are interwoven with issues in Polyhedron, Bellman equation, Quadratic equation, Finite set and Piecewise affine. David Q. Mayne focuses mostly in the field of Robust control, narrowing it down to topics relating to Nonlinear control and, in certain cases, Constrained optimization. His Nonlinear system research is multidisciplinary, incorporating elements of Stability and Robustness.

Between 2001 and 2021, his most popular works were:

  • Robust model predictive control of constrained linear systems with bounded disturbances (893 citations)
  • Model Predictive Control (801 citations)
  • Constrained state estimation for nonlinear discrete-time systems: stability and moving horizon approximations (628 citations)

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

  • Mathematical analysis
  • Control theory
  • Statistics

His scientific interests lie mostly in Model predictive control, Control theory, Robust control, Optimal control and Mathematical optimization. His work carried out in the field of Model predictive control brings together such families of science as Discrete time and continuous time, Exponential stability, Nonlinear system, Control theory and Robustness. His Robust control research incorporates themes from Nonlinear control, Linear system, Quadratic programming, Finite set and Bounded function.

In Linear system, David Q. Mayne works on issues like Linear-quadratic-Gaussian control, which are connected to Adaptive control. David Q. Mayne interconnects Piecewise affine and Bellman equation in the investigation of issues within Optimal control. Constrained optimization is the focus of his Mathematical optimization research.

Best Publications

  • Survey Constrained model predictive control: Stability and optimality

    D. Q. Mayne;J. B. Rawlings;C. V. Rao;P. O. M. Scokaert

  • Receding horizon control of nonlinear systems

    D.Q. Mayne;H. Michalska

  • Robust model predictive control of constrained linear systems with bounded disturbances

    D. Q. Mayne;M. M. Seron;S. V. Raković

  • Model Predictive Control

    David Q. Mayne

  • Robust receding horizon control of constrained nonlinear systems

    H. Michalska;D.Q. Mayne

  • Min-max feedback model predictive control for constrained linear systems

    P.O.M. Scokaert;D.Q. Mayne

  • Constrained state estimation for nonlinear discrete-time systems: stability and moving horizon approximations

    C.V. Rao;J.B. Rawlings;D.Q. Mayne

  • Invariant approximations of the minimal robust positively Invariant set

    S.V. Rakovic;E.C. Kerrigan;K.I. Kouramas;D.Q. Mayne

  • Suboptimal model predictive control (feasibility implies stability)

    P.O.M. Scokaert;D.Q. Mayne;J.B. Rawlings

  • Robust model predictive control using tubes

    W. Langson;I. Chryssochoos;S. V. Raković;D. Q. Mayne

  • Design issues in adaptive control

    R.H. Middleton;G.C. Goodwin;D.J. Hill;D.Q. Mayne

  • Robust output feedback model predictive control of constrained linear systems

    D. Q. Mayne;S. V. Raković;R. Findeisen;F. AllgöWer

  • A parameter estimation perspective of continuous time model reference adaptive control

    G C Goodwin;D Q Mayne

  • Applications of hysteresis switching in parameter adaptive control

    A.S. Morse;D.Q. Mayne;G.C. Goodwin

  • A Second-order Gradient Method for Determining Optimal Trajectories of Non-linear Discrete-time Systems

    David Mayne

  • Tube-based robust nonlinear model predictive control

    D. Q. Mayne;E. C. Kerrigan;E. J. van Wyk;P. Falugi

  • Moving horizon observers and observer-based control

    H. Michalska;D.Q. Mayne

  • Monte Carlo techniques to estimate the conditional expectation in multi-stage non-linear filtering†

    J. E. Handschin;D. Q. Mayne

  • Rapprochement between continuous and discrete model reference adaptive control

    G C Goodwin;R L Leal;D Q Mayne;R H Middleton

  • Control of Constrained Dynamic Systems

    David Q. Mayne

  • Correspondence: Correction to Constrained model predictive control: stability and optimality

    D.Q Mayne;J.B Rawlings

Frequent Co-Authors

Elijah Polak
Elijah Polak University of California, Berkeley
Graham C. Goodwin
Graham C. Goodwin University of Newcastle Australia
Eric C. Kerrigan
Eric C. Kerrigan Imperial College London
James B. Rawlings
James B. Rawlings University of California, Santa Barbara
Maria M. Seron
Maria M. Seron University of Newcastle Australia
Karl Johan Åström
Karl Johan Åström Lund University
Frank Allgöwer
Frank Allgöwer University of Stuttgart
Rolf Findeisen
Rolf Findeisen Technical University of Darmstadt
Wolfgang Marquardt
Wolfgang Marquardt RWTH Aachen University
Eric Rogers
Eric Rogers University of Southampton

External Links

Wikipedia of David Q. Mayne Personal website of David Q. Mayne Google Scholar page

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