J. Fraser Forbes

2.9k total citations
111 papers, 2.2k citations indexed

About

J. Fraser Forbes is a scholar working on Control and Systems Engineering, Computational Theory and Mathematics and Statistics, Probability and Uncertainty. According to data from OpenAlex, J. Fraser Forbes has authored 111 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 97 papers in Control and Systems Engineering, 20 papers in Computational Theory and Mathematics and 15 papers in Statistics, Probability and Uncertainty. Recurrent topics in J. Fraser Forbes's work include Advanced Control Systems Optimization (62 papers), Fault Detection and Control Systems (36 papers) and Stability and Controllability of Differential Equations (24 papers). J. Fraser Forbes is often cited by papers focused on Advanced Control Systems Optimization (62 papers), Fault Detection and Control Systems (36 papers) and Stability and Controllability of Differential Equations (24 papers). J. Fraser Forbes collaborates with scholars based in Canada, Qatar and Norway. J. Fraser Forbes's co-authors include Thomas E. Marlin, Martin Guay, Ilyasse Aksikas, Yale Zhang, Biao Huang, Adrian Fuxman, Michael G. Forbes, Stevan Dubljević, Vinay Kariwala and John F. MacGregor and has published in prestigious journals such as Biomaterials, Chemical Engineering Journal and Automatica.

In The Last Decade

J. Fraser Forbes

106 papers receiving 2.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
J. Fraser Forbes Canada 26 1.6k 250 219 148 144 111 2.2k
Ricardo Sánchez‐Peña Argentina 25 1.0k 0.6× 115 0.5× 118 0.5× 81 0.5× 218 1.5× 108 2.4k
Martin Horn Austria 25 1.4k 0.9× 507 2.0× 78 0.4× 119 0.8× 115 0.8× 279 2.7k
Fen Wu United States 33 4.1k 2.5× 327 1.3× 472 2.2× 228 1.5× 227 1.6× 205 5.1k
Nael H. El‐Farra United States 34 3.8k 2.3× 291 1.2× 327 1.5× 145 1.0× 305 2.1× 165 4.6k
Thomas A. Badgwell United States 13 4.0k 2.5× 396 1.6× 159 0.7× 188 1.3× 107 0.7× 31 4.6k
Prashant Mhaskar Canada 36 3.8k 2.4× 591 2.4× 202 0.9× 180 1.2× 297 2.1× 190 4.6k
Gabriele Pannocchia Italy 22 2.0k 1.2× 304 1.2× 58 0.3× 62 0.4× 106 0.7× 118 2.5k
John Bagterp Jørgensen Denmark 32 1.7k 1.1× 480 1.9× 76 0.3× 164 1.1× 63 0.4× 268 3.6k
Tapio Westerlund Finland 25 1.1k 0.7× 199 0.8× 431 2.0× 121 0.8× 80 0.6× 100 2.2k
Bram de Jager Netherlands 28 1.1k 0.7× 736 2.9× 134 0.6× 62 0.4× 155 1.1× 187 2.7k

Countries citing papers authored by J. Fraser Forbes

Since Specialization
Citations

This map shows the geographic impact of J. Fraser Forbes's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by J. Fraser Forbes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. Fraser Forbes more than expected).

Fields of papers citing papers by J. Fraser Forbes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J. Fraser Forbes. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by J. Fraser Forbes. The network helps show where J. Fraser Forbes may publish in the future.

Co-authorship network of co-authors of J. Fraser Forbes

This figure shows the co-authorship network connecting the top 25 collaborators of J. Fraser Forbes. A scholar is included among the top collaborators of J. Fraser Forbes based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with J. Fraser Forbes. J. Fraser Forbes is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Aksikas, Ilyasse, et al.. (2018). Model-based optimal boundary control of selective catalytic reduction in diesel-powered vehicles. Journal of Process Control. 71. 63–74. 5 indexed citations
3.
Liu, Jinfeng, et al.. (2017). A Bilevel Optimization Approach to Coordination of Distributed Model Predictive Control Systems. Industrial & Engineering Chemistry Research. 57(5). 1516–1530. 1 indexed citations
4.
Yin, Xunyuan, et al.. (2017). Coordinated distributed moving horizon state estimation for linear systems based on prediction‐driven method. The Canadian Journal of Chemical Engineering. 95(10). 1953–1967. 1 indexed citations
5.
Aksikas, Ilyasse, et al.. (2015). Optimal boundary control of coupled parabolic PDE–ODE systems using infinite-dimensional representation. Journal of Process Control. 33. 102–111. 25 indexed citations
6.
Jomha, Nadr M., Janet A.W. Elliott, Garson K. Law, et al.. (2012). Vitrification of intact human articular cartilage. Biomaterials. 33(26). 6061–6068. 60 indexed citations
7.
Forbes, J. Fraser, et al.. (2012). Stability analysis and regularization of uncertain linear multi-objective integer optimization problems. Engineering Optimization. 44(11). 1279–1302.
8.
Dubljević, Stevan, et al.. (2010). Robust characteristic-based MPC of a fixed-bed reactor. 4421–4426. 6 indexed citations
9.
Aksikas, Ilyasse, et al.. (2009). Optimal control of a time-varying catalytic fixed bed reactor with catalyst deactivation. 2470–2475. 4 indexed citations
10.
Forbes, J. Fraser, et al.. (2009). Coordination of Distributed Model Predictive Controllers for Constrained Dynamic Processes. IFAC Proceedings Volumes. 42(11). 135–140. 14 indexed citations
11.
Aksikas, Ilyasse, Adrian Fuxman, & J. Fraser Forbes. (2008). Control of Time-Varying Distributed Parameter Plug Flow Reactor by LQR. IFAC Proceedings Volumes. 41(2). 11955–11960. 1 indexed citations
12.
Fuxman, Adrian, et al.. (2007). Repetitive model predictive control of a reverse flow reactor. Chemical Engineering Science. 62(8). 2154–2167. 23 indexed citations
13.
Forbes, J. Fraser, et al.. (2005). A stochastic optimization approach to mine truck allocation. International Journal of Surface Mining Reclamation and Environment. 19(3). 162–175. 67 indexed citations
14.
Forbes, Michael G., Martin Guay, & J. Fraser Forbes. (2005). Probabilistic control design for continuous-time stochastic nonlinear systems: a PDF-shaping approach. 32. 132–136. 8 indexed citations
15.
Forbes, Michael G., J. Fraser Forbes, & Martin Guay. (2005). Control design to shape the stationary probability density function. Transactions of the Institute of Measurement and Control. 27(5). 331–346. 4 indexed citations
16.
Shang, Helen, J. B. Wiskel, J. Fraser Forbes, & H. Henein. (2003). Exploiting model fidelity to control metals processing. JOM. 55(3). 41–45. 2 indexed citations
17.
Forbes, J. Fraser, et al.. (2003). Determining controller benefits via probabilistic optimization. International Journal of Adaptive Control and Signal Processing. 17(7-9). 553–568. 21 indexed citations
18.
Guay, Martin, et al.. (2003). Sensor selection for model-based real-time optimization: relating design of experiments and design cost. Journal of Process Control. 13(7). 667–678. 23 indexed citations
19.
Forbes, J. Fraser, et al.. (2000). Constrained Optimization of Nonlinear, Dynamic Chemical Processes – A Normalized Form Approach. IFAC Proceedings Volumes. 33(10). 767–772. 6 indexed citations
20.
Forbes, J. Fraser, et al.. (1997). Approximation of High-Dimensional Multivariable Controllers using Semi-Definite Programming. IFAC Proceedings Volumes. 30(9). 703–708.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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