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
Electronics and Electrical Engineering D-index 58 Citations 14,574 309 World Ranking 664 National Ranking 16

Overview

What is he best known for?

The fields of study he is best known for:

  • Control theory
  • Artificial intelligence
  • Mathematical optimization

Control theory, Mathematical optimization, Model predictive control, Optimal control and Nonlinear system are his primary areas of study. His work deals with themes such as Robot kinematics, Iterative method, Computation and Motion control, which intersect with Control theory. His Mathematical optimization research incorporates elements of Convex function, Nonlinear programming, Robustness and Convex optimization.

His Model predictive control research incorporates themes from Nonlinear control, Control engineering, Algorithm, Software and Solver. He interconnects Robust optimization, Optimization problem, Set and Pareto principle in the investigation of issues within Optimal control. His research in Nonlinear system intersects with topics in Differential algebraic equation, Wind speed, Power and Direct multiple shooting method.

His most cited work include:

  • ACADO toolkit—An open-source framework for automatic control and dynamic optimization (641 citations)
  • qpOASES: a parametric active-set algorithm for quadratic programming (610 citations)
  • Real-time optimization and nonlinear model predictive control of processes governed by differential-algebraic equations (549 citations)

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

Moritz Diehl spends much of his time researching Control theory, Model predictive control, Mathematical optimization, Optimal control and Nonlinear system. His Control theory research focuses on Wind power and how it relates to Aerospace engineering, Airfoil, Energy and Wind speed. His Model predictive control research is multidisciplinary, incorporating perspectives in Control engineering, Algorithm, Nonlinear model and Solver.

His Mathematical optimization study integrates concerns from other disciplines, such as Nonlinear programming and Convex optimization. His Optimal control research is multidisciplinary, incorporating elements of Discretization, Power, Robust control and Direct multiple shooting method. The various areas that Moritz Diehl examines in his Nonlinear system study include Estimation theory, Computation and Applied mathematics.

He most often published in these fields:

  • Control theory (45.45%)
  • Model predictive control (40.53%)
  • Mathematical optimization (38.07%)

What were the highlights of his more recent work (between 2017-2021)?

  • Model predictive control (40.53%)
  • Control theory (45.45%)
  • Mathematical optimization (38.07%)

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

His primary areas of study are Model predictive control, Control theory, Mathematical optimization, Optimal control and Applied mathematics. His Model predictive control study combines topics from a wide range of disciplines, such as Stability, Nonlinear model, Nonlinear system, Control theory and Extension. His work in Nonlinear system addresses subjects such as Computation, which are connected to disciplines such as Software.

His work on Trajectory as part of general Control theory research is frequently linked to Central processing unit, Grey box model and Flux linkage, thereby connecting diverse disciplines of science. Moritz Diehl combines subjects such as Homotopy, Collision avoidance and Motion planning with his study of Mathematical optimization. His studies deal with areas such as Wind power, Actuator, Algorithm and Sequential quadratic programming as well as Optimal control.

Between 2017 and 2021, his most popular works were:

  • CasADi: a software framework for nonlinear optimization and optimal control (543 citations)
  • From linear to nonlinear MPC: bridging the gap via the real-time iteration (81 citations)
  • In-Vehicle Realization of Nonlinear MPC for Gasoline Two-Stage Turbocharging Airpath Control (31 citations)

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

  • Artificial intelligence
  • Control theory
  • Quantum mechanics

His scientific interests lie mostly in Model predictive control, Optimal control, Mathematical optimization, Nonlinear system and Algorithm. His Model predictive control research includes elements of Control theory, Nonlinear model, Quadratic programming, Software and Contraction. His work on Stability and Control theory as part of general Control theory study is frequently linked to Software framework, bridging the gap between disciplines.

Moritz Diehl has researched Optimal control in several fields, including Nonlinear programming, Battery, Integer, Differential equation and Stochastic model predictive control. His Mathematical optimization study combines topics in areas such as Nonlinear dynamic systems, Motion planning and Motion. His studies in Algorithm integrate themes in fields like Initialization and Trajectory.

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

ACADO toolkit—An open-source framework for automatic control and dynamic optimization

Boris Houska;Hans Joachim Ferreau;Moritz Diehl.
Optimal Control Applications & Methods (2011)

880 Citations

qpOASES: a parametric active-set algorithm for quadratic programming

Hans Joachim Ferreau;Christian Kirches;Andreas Potschka;Hans Georg Bock.
Mathematical Programming Computation (2014)

785 Citations

Real-time optimization and nonlinear model predictive control of processes governed by differential-algebraic equations

Moritz Diehl;H.Georg Bock;Johannes P. Schlöder;Rolf Findeisen.
Journal of Process Control (2002)

764 Citations

CasADi: a software framework for nonlinear optimization and optimal control

Joel A. E. Andersson;Joris Gillis;Greg Horn;James B. Rawlings.
Mathematical Programming Computation (2019)

731 Citations

An online active set strategy to overcome the limitations of explicit MPC

Hans Joachim Ferreau;H. G Bock;Moritz Diehl.
International Journal of Robust and Nonlinear Control (2008)

654 Citations

Efficient Numerical Methods for Nonlinear MPC and Moving Horizon Estimation

Moritz Diehl;Hans Joachim Ferreau;Niels Haverbeke.
Lecture Notes in Control and Information Sciences (2009)

552 Citations

A Lyapunov Function for Economic Optimizing Model Predictive Control

M Diehl;R Amrit;J B Rawlings.
IEEE Transactions on Automatic Control (2011)

524 Citations

A Real-Time Iteration Scheme for Nonlinear Optimization in Optimal Feedback Control

Moritz Diehl;Hans Georg Bock;Johannes P. Schlöder.
Siam Journal on Control and Optimization (2005)

500 Citations

Time-Optimal Path Tracking for Robots: A Convex Optimization Approach

D. Verscheure;B. Demeulenaere;J. Swevers;J. De Schutter.
IEEE Transactions on Automatic Control (2009)

448 Citations

An auto-generated real-time iteration algorithm for nonlinear MPC in the microsecond range

Boris Houska;Hans Joachim Ferreau;Moritz Diehl.
Automatica (2011)

381 Citations

Best Scientists Citing Moritz Diehl

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Sebastian Engell

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Lorenzo Fagiano

Politecnico di Milano

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Lorenz T. Biegler

Lorenz T. Biegler

Carnegie Mellon University

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Colin N. Jones

Colin N. Jones

École Polytechnique Fédérale de Lausanne

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Rolf Findeisen

Rolf Findeisen

Otto-von-Guericke University Magdeburg

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Manfred Morari

University of Pennsylvania

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Ilya Kolmanovsky

Ilya Kolmanovsky

University of Michigan–Ann Arbor

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Tor Arne Johansen

Tor Arne Johansen

Norwegian University of Science and Technology

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Victor M. Zavala

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University of Wisconsin–Madison

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Panagiotis D. Christofides

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Wolfgang Marquardt

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Lars Grüne

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Alberto Bemporad

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Marc Moonen

Marc Moonen

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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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