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
Engineering and Technology D-index 33 Citations 5,317 213 World Ranking 4351 National Ranking 85

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer network
  • Electrical engineering

His primary areas of investigation include Model predictive control, Control engineering, Control, Control theory and Control theory. Rudy R. Negenborn undertakes multidisciplinary studies into Model predictive control and Scheme in his work. His study in Control engineering is interdisciplinary in nature, drawing from both Electricity, Extended Kalman filter, Energy consumption, Multi-agent system and Benchmark.

In general Control study, his work on Distributed model predictive control often relates to the realm of Partially observable Markov decision process, thereby connecting several areas of interest. His Control theory research incorporates elements of Voltage regulation and Power control. He has included themes like Computational complexity theory, Quadratic programming, Mathematical optimization, Decentralised system and Trajectory in his Control theory study.

His most cited work include:

  • Multi-agent model predictive control for transportation networks: Serial versus parallel schemes (209 citations)
  • Demand Response With Micro-CHP Systems (180 citations)
  • Distributed Model Predictive Control: An Overview and Roadmap of Future Research Opportunities (176 citations)

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

His primary scientific interests are in Model predictive control, Control, Control theory, Container and Operations research. His research integrates issues of Control engineering, Control theory and Optimization problem, Mathematical optimization in his study of Model predictive control. His work carried out in the field of Control engineering brings together such families of science as Electricity, Electric power system, Energy consumption, Distributed model predictive control and Benchmark.

He interconnects Power, Systems engineering and Multi-agent system, Multi agent model in the investigation of issues within Control. His Control theory research includes elements of Collision avoidance and Motion control. His research on Container also deals with topics like

  • Terminal that intertwine with fields like Port and Distributed computing,
  • Flow network which connect with Default gateway and Service.

He most often published in these fields:

  • Model predictive control (40.08%)
  • Control (19.47%)
  • Control theory (18.70%)

What were the highlights of his more recent work (between 2019-2021)?

  • Model predictive control (40.08%)
  • Control theory (18.70%)
  • Mathematical optimization (12.98%)

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

Model predictive control, Control theory, Mathematical optimization, Truck and Container are his primary areas of study. His studies in Model predictive control integrate themes in fields like State-space representation, Optimization problem and Industrial organization. His Underactuation, Optimal control and PID controller study in the realm of Control theory interacts with subjects such as Observable.

The various areas that Rudy R. Negenborn examines in his Truck study include Routing and Operations research. Rudy R. Negenborn combines subjects such as Distributed computing, Port, Terminal and Platoon with his study of Container. His work in Control covers topics such as Automation which are related to areas like Collision avoidance.

Between 2019 and 2021, his most popular works were:

  • Ship collision avoidance methods : State-of-the-art (53 citations)
  • Cooperative Multi-Vessel Systems in Urban Waterway Networks (8 citations)
  • Automatic Docking for Underactuated Ships Based on Multi-Objective Nonlinear Model Predictive Control (4 citations)

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

  • Artificial intelligence
  • Computer network
  • Electrical engineering

His primary areas of study are Matching, Operations research, Truck, Mathematical optimization and Train. His Operations research research integrates issues from Baseline and Flow network. His Mathematical optimization research includes themes of Canal network, Road networks and Path following.

In his study, Rudy R. Negenborn carries out multidisciplinary Performance indicator and Distributed computing research. His work deals with themes such as Linear programming and Terminal, which intersect with Distributed computing. The concepts of his Container study are interwoven with issues in Port and Process.

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

Design and control of hybrid power and propulsion systems for smart ships: A review of developments

R.D. Geertsma;R.R. Negenborn;K. Visser;J.J. Hopman.
Applied Energy (2017)

327 Citations

Distributed Model Predictive Control Made Easy

Jos M. Maestre;Rudy R. Negenborn.
Published in <b>2014</b> by Springer (2013)

311 Citations

Multi-agent model predictive control for transportation networks: Serial versus parallel schemes

R. R. Negenborn;B. De Schutter;J. Hellendoorn.
Engineering Applications of Artificial Intelligence (2008)

284 Citations

Distributed Model Predictive Control: An Overview and Roadmap of Future Research Opportunities

R.R. Negenborn;J.M. Maestre.
IEEE Control Systems Magazine (2014)

282 Citations

Demand Response With Micro-CHP Systems

Michiel Houwing;Rudy R Negenborn;Bart De Schutter.
Proceedings of the IEEE (2011)

276 Citations

Distributed model predictive control of irrigation canals

Rudy R. Negenborn;Peter-Jules van Overloop;Tamás Keviczky;Bart De Schutter.
Networks and Heterogeneous Media (2009)

248 Citations

A comparative analysis of distributed MPC techniques applied to the HD-MPC four-tank benchmark

I. Alvarado;D. Limon;D. Muñoz de la Peña;J.M. Maestre.
Journal of Process Control (2011)

200 Citations

Multi-agent model predictive control with applications to power networks

R.R. Negenborn.
(2007)

170 Citations

Robot Localization and Kalman Filters

Rudy Negenborn.
(2003)

156 Citations

Ship collision avoidance methods : State-of-the-art

Yamin Huang;Linying Chen;Pengfei Chen;Rudy R. Negenborn.
Safety Science (2020)

115 Citations

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

Contact us

Best Scientists Citing Rudy R. Negenborn

Bart De Schutter

Bart De Schutter

Delft University of Technology

Publications: 41

Eduardo F. Camacho

Eduardo F. Camacho

University of Seville

Publications: 33

Vicenç Puig

Vicenç Puig

Universitat Politècnica de Catalunya

Publications: 26

Riccardo Scattolini

Riccardo Scattolini

Politecnico di Milano

Publications: 22

Carlos Bordons

Carlos Bordons

University of Seville

Publications: 21

Joao P. S. Catalao

Joao P. S. Catalao

University of Porto

Publications: 17

Mahmoud-Reza Haghifam

Mahmoud-Reza Haghifam

Tarbiat Modares University

Publications: 14

Karl Henrik Johansson

Karl Henrik Johansson

Royal Institute of Technology

Publications: 12

Alberto Bemporad

Alberto Bemporad

IMT Institute for Advanced Studies Lucca

Publications: 11

B. De Schutter

B. De Schutter

Delft University of Technology

Publications: 11

Miadreza Shafie-khah

Miadreza Shafie-khah

University of Vaasa

Publications: 11

Shaoyuan Li

Shaoyuan Li

Wuhan University

Publications: 10

Josep M. Guerrero

Josep M. Guerrero

Aalborg University

Publications: 10

Goran Andersson

Goran Andersson

ETH Zurich

Publications: 10

Frank Allgöwer

Frank Allgöwer

University of Stuttgart

Publications: 10

Prodromos Daoutidis

Prodromos Daoutidis

University of Minnesota

Publications: 9

Something went wrong. Please try again later.