What is he best known for?
The fields of study he is best known for:
- Electrical engineering
- Control theory
- Voltage
His primary areas of study are Microgrid, Control theory, Control engineering, Control theory and Energy storage.
His Microgrid research integrates issues from State of charge, Distributed generation, Voltage droop and Telecommunications network.
His Control theory study combines topics in areas such as Converters, AC power, Voltage and Model predictive control.
His Control engineering research is multidisciplinary, incorporating perspectives in Battery, Control and Power control.
His work is dedicated to discovering how Control theory, Electric power system are connected with Electrical engineering and Reliability and other disciplines.
His Energy storage research is multidisciplinary, incorporating elements of Photovoltaic system and Renewable energy.
His most cited work include:
- DC Microgrids—Part I: A Review of Control Strategies and Stabilization Techniques (616 citations)
- DC Microgrids—Part II: A Review of Power Architectures, Applications, and Standardization Issues (488 citations)
- Supervisory Control of an Adaptive-Droop Regulated DC Microgrid With Battery Management Capability (470 citations)
What are the main themes of his work throughout his whole career to date?
Tomislav Dragicevic mainly investigates Control theory, Microgrid, Model predictive control, Control theory and Voltage.
Tomislav Dragicevic has included themes like Voltage droop, Voltage source, Converters and Electric power system in his Control theory study.
The Microgrid study combines topics in areas such as Control engineering, Control system, Distributed generation and Energy storage.
His Energy storage research includes themes of Power control, Battery, State of charge and Photovoltaic system, Electrical engineering.
In his study, which falls under the umbrella issue of Model predictive control, Artificial neural network is strongly linked to Power electronics.
Tomislav Dragicevic combines subjects such as Compensation, Fuzzy logic and Nonlinear system with his study of Control theory.
He most often published in these fields:
- Control theory (51.18%)
- Microgrid (34.34%)
- Model predictive control (23.57%)
What were the highlights of his more recent work (between 2019-2021)?
- Control theory (51.18%)
- Model predictive control (23.57%)
- Microgrid (34.34%)
In recent papers he was focusing on the following fields of study:
Tomislav Dragicevic focuses on Control theory, Model predictive control, Microgrid, Converters and Control theory.
His Control theory research is mostly focused on the topic Control system.
His Model predictive control study incorporates themes from Discretization, Electronic component, Inductor and Energy storage.
Tomislav Dragicevic has researched Microgrid in several fields, including Electrical impedance, Electric vehicle, Voltage droop and Photovoltaic system.
Tomislav Dragicevic interconnects Control engineering, Artificial neural network, Electronic engineering and Renewable energy in the investigation of issues within Converters.
The study incorporates disciplines such as Automatic frequency control, Oscillation, Nonlinear system, Boost converter and Robustness in addition to Control theory.
Between 2019 and 2021, his most popular works were:
- On the Secondary Control Architectures of AC Microgrids: An Overview (45 citations)
- The Future 5G Network-Based Secondary Load Frequency Control in Shipboard Microgrids (29 citations)
- Anti-Islanding Protection of PV-Based Microgrids Consisting of PHEVs Using SVMs (22 citations)
In his most recent research, the most cited papers focused on:
- Electrical engineering
- Control theory
- Voltage
Control theory, Model predictive control, Voltage, Converters and Control theory are his primary areas of study.
His research in Control theory intersects with topics in Electric power system, LC circuit, Capacitor, Space vector modulation and Microgrid.
His study in Microgrid is interdisciplinary in nature, drawing from both Control system, Distributed generation, Artificial neural network, Discretization and Photovoltaic system.
His Model predictive control research includes elements of Power electronics, Voltage source, Voltage regulation and Robustness.
The concepts of his Converters study are interwoven with issues in Control engineering, Passivity and Electronic engineering.
His Control theory study incorporates themes from Injection attacks, Fault detection and isolation, Oscillation, Fuzzy logic and Optimization problem.
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.
