D-Index & Metrics Best Publications

D-Index & Metrics 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.

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 30 Citations 4,408 161 World Ranking 7849 National Ranking 294

Overview

What is he best known for?

The fields of study he is best known for:

  • Control theory
  • Electrical engineering
  • Quantum mechanics

Lorenzo Fagiano mostly deals with Model predictive control, Control theory, Mathematical optimization, Wind power and Optimal control. His work is dedicated to discovering how Model predictive control, Linear system are connected with Stability and other disciplines. His research related to Robust control and Nonlinear control might be considered part of Control theory.

His Mathematical optimization study deals with Randomized algorithm intersecting with Nonlinear system. He has researched Wind power in several fields, including Energy, Aerospace engineering, Automotive engineering and Renewable energy. Within one scientific family, Lorenzo Fagiano focuses on topics pertaining to Scenario optimization under Optimal control, and may sometimes address concerns connected to Computational complexity theory, Robustness and Optimization problem.

His most cited work include:

  • High Altitude Wind Energy Generation Using Controlled Power Kites (171 citations)
  • Robust Model Predictive Control via Scenario Optimization (160 citations)
  • The scenario approach for Stochastic Model Predictive Control with bounds on closed-loop constraint violations (158 citations)

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

Lorenzo Fagiano focuses on Control theory, Wind power, Model predictive control, Mathematical optimization and Nonlinear system. Lorenzo Fagiano works mostly in the field of Control theory, limiting it down to concerns involving Control engineering and, occasionally, Yaw and Control system. He has researched Wind power in several fields, including Power, Aerodynamics, Aerospace engineering, Wing and Wind speed.

As part of the same scientific family, Lorenzo Fagiano usually focuses on Model predictive control, concentrating on Linear system and intersecting with Algorithm. His work on Optimal control and Optimization problem as part of his general Mathematical optimization study is frequently connected to Convex optimization and Constraint satisfaction, thereby bridging the divide between different branches of science. His Optimal control research incorporates elements of Robustness and Scenario optimization.

He most often published in these fields:

  • Control theory (48.65%)
  • Wind power (35.68%)
  • Model predictive control (38.92%)

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

  • Model predictive control (38.92%)
  • Set (19.46%)
  • Mathematical optimization (32.97%)

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

His primary scientific interests are in Model predictive control, Set, Mathematical optimization, Linear system and Control theory. He interconnects Predictive modelling and Control theory in the investigation of issues within Model predictive control. Mathematical optimization is closely attributed to Routing in his work.

His work in Linear system addresses issues such as Algorithm, which are connected to fields such as Noise measurement and Recurrent neural network. His study in the field of Nonlinear system is also linked to topics like Process. His Nonlinear system study incorporates themes from Dynamical systems theory and Scenario optimization.

Between 2017 and 2021, his most popular works were:

  • Future emerging technologies in the wind power sector: A European perspective (35 citations)
  • Autonomous Takeoff and Flight of a Tethered Aircraft for Airborne Wind Energy (16 citations)
  • Adaptive model predictive control for linear time varying MIMO systems (16 citations)

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

  • Electrical engineering
  • Control theory
  • Quantum mechanics

Lorenzo Fagiano mainly focuses on Model predictive control, Convergence, Set, Control theory and Mathematical optimization. In his papers, Lorenzo Fagiano integrates diverse fields, such as Model predictive control and Sequence. His Control theory study frequently draws parallels with other fields, such as Propeller.

His Propeller research focuses on Flight control surfaces and how it connects with Wind power. His study in Mathematical optimization is interdisciplinary in nature, drawing from both Microgrid and Energy market. His Robustness research is multidisciplinary, incorporating elements of Elevator, Aileron, Takeoff and Winch.

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

High Altitude Wind Energy Generation Using Controlled Power Kites

M. Canale;L. Fagiano;M. Milanese.
IEEE Transactions on Control Systems and Technology (2010)

248 Citations

Robust Model Predictive Control via Scenario Optimization

Giuseppe C. Calafiore;L. Fagiano.
IEEE Transactions on Automatic Control (2013)

240 Citations

The scenario approach for Stochastic Model Predictive Control with bounds on closed-loop constraint violations

Georg Schildbach;Lorenzo Fagiano;Christoph Frei;Manfred Morari.
Automatica (2014)

225 Citations

Automatic Crosswind Flight of Tethered Wings for Airborne Wind Energy: Modeling, Control Design, and Experimental Results

Lorenzo Fagiano;Aldo U. Zgraggen;Manfred Morari;Mustafa Khammash.
IEEE Transactions on Control Systems and Technology (2014)

176 Citations

Vehicle Yaw Control via Second-Order Sliding-Mode Technique

M. Canale;L. Fagiano;A. Ferrara;C. Vecchio.
IEEE Transactions on Industrial Electronics (2008)

175 Citations

Power Kites for Wind Energy Generation [Applications of Control]

Massimo Canale;Lorenzo Fagiano;Mario Milanese.
IEEE Control Systems Magazine (2007)

162 Citations

Robust vehicle yaw control using an active differential and IMC techniques

Massimo Canale;Lorenzo Fagiano;Mario Milanese;P. Borodani.
Control Engineering Practice (2007)

159 Citations

KiteGen : A revolution in wind energy generation

Massimo Canale;Lorenzo Fagiano;Mario Milanese.
Energy (2009)

135 Citations

Generalized terminal state constraint for model predictive control

Lorenzo Fagiano;Lorenzo Fagiano;Andrew R. Teel.
Automatica (2013)

133 Citations

Airborne Wind Energy: An overview

L. Fagiano;M. Milanese.
advances in computing and communications (2012)

131 Citations

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