What is he best known for?
The fields of study he is best known for:
- Control theory
- Artificial intelligence
- Programming language
Alberto Bemporad spends much of his time researching Model predictive control, Mathematical optimization, Control theory, Hybrid system and Linear system.
His research integrates issues of Control system, Control engineering, Norm, Open-loop controller and Robustness in his study of Model predictive control.
His Mathematical optimization research incorporates themes from Piecewise linear function and Algorithm.
In his study, which falls under the umbrella issue of Control theory, Teleoperation, Synchronization, Telerobotics and Control logic is strongly linked to State.
His Hybrid system research is multidisciplinary, incorporating elements of Automaton, Theoretical computer science, Dynamical systems theory, Algebra and Integer programming.
His studies deal with areas such as State variable, Estimation and Lyapunov function, Nonlinear system as well as Linear system.
His most cited work include:
- The explicit linear quadratic regulator for constrained systems (2502 citations)
- Control of systems integrating logic, dynamics, and constraints (2430 citations)
- Robust model predictive control: A survey (756 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Model predictive control, Control theory, Mathematical optimization, Hybrid system and Optimal control.
His Model predictive control research includes elements of Control system, Linear system, Exponential stability, Control engineering and Algorithm.
Alberto Bemporad combines subjects such as Piecewise linear function and Set with his study of Control theory.
His Mathematical optimization research is multidisciplinary, relying on both Function and Quadratic equation.
His biological study spans a wide range of topics, including Automaton, Dynamical systems theory, Discrete time and continuous time, Computation and Integer programming.
Alberto Bemporad studies Linear-quadratic-Gaussian control, a branch of Optimal control.
He most often published in these fields:
- Model predictive control (49.21%)
- Control theory (43.90%)
- Mathematical optimization (40.55%)
What were the highlights of his more recent work (between 2015-2021)?
- Mathematical optimization (40.55%)
- Model predictive control (49.21%)
- Control theory (43.90%)
In recent papers he was focusing on the following fields of study:
Alberto Bemporad mostly deals with Mathematical optimization, Model predictive control, Control theory, Quadratic programming and Nonlinear system.
His Mathematical optimization study incorporates themes from Quadratic equation and Transaction cost.
His study in Model predictive control is interdisciplinary in nature, drawing from both Control system, Linear system, Control engineering, Control theory and Algorithm.
His work on Stability as part of general Control theory research is frequently linked to Horizon, thereby connecting diverse disciplines of science.
His Quadratic programming study also includes fields such as
- Matrix decomposition most often made with reference to Solver,
- Branch and bound, which have a strong connection to Integer.
Alberto Bemporad interconnects Artificial neural network, Stochastic gradient descent, Process and Bounded function in the investigation of issues within Nonlinear system.
Between 2015 and 2021, his most popular works were:
- Predictive Control for Linear and Hybrid Systems (498 citations)
- Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities (109 citations)
- OSQP: An Operator Splitting Solver for Quadratic Programs (109 citations)
In his most recent research, the most cited papers focused on:
- Control theory
- Artificial intelligence
- Programming language
His primary areas of investigation include Model predictive control, Mathematical optimization, Control theory, Quadratic programming and Solver.
The various areas that Alberto Bemporad examines in his Model predictive control study include Optimal control, Control engineering, Automotive engineering, Nonlinear system and Robustness.
He has researched Control engineering in several fields, including Hybrid system and Matlab toolbox.
His work on Global optimization as part of general Mathematical optimization research is frequently linked to Inverse distance weighting, bridging the gap between disciplines.
Alberto Bemporad is studying Control theory, which is a component of Control theory.
His studies in Quadratic programming integrate themes in fields like Algorithm, Branch and bound, Sparse matrix and Set.
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.
