What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Control theory
- Machine learning
Radu-Emil Precup mainly focuses on Control theory, Fuzzy logic, Fuzzy control system, Servomechanism and Optimization problem.
Radu-Emil Precup regularly ties together related areas like Fuzzy number in his Control theory studies.
The concepts of his Fuzzy logic study are interwoven with issues in Stability, Lyapunov function and Mathematical optimization.
His biological study spans a wide range of topics, including Variable, Iterative method, Settling time and Adaptive control.
His Servomechanism research includes elements of Mechatronics, Optimal control and Sensitivity.
His Optimization problem course of study focuses on Search algorithm and Fitness function and Constrained optimization.
His most cited work include:
- Survey paper: A survey on industrial applications of fuzzy control (346 citations)
- Technical Communique: An extension of tuning relations after symmetrical optimum method for PI and PID controllers (201 citations)
- Grey Wolf Optimizer Algorithm-Based Tuning of Fuzzy Control Systems With Reduced Parametric Sensitivity (127 citations)
What are the main themes of his work throughout his whole career to date?
Radu-Emil Precup mostly deals with Control theory, Fuzzy logic, Fuzzy control system, Control engineering and Control system.
Radu-Emil Precup combines topics linked to Optimization problem with his work on Control theory.
His Fuzzy logic research includes themes of Lyapunov function and Mathematical optimization.
Radu-Emil Precup has included themes like Stability, Transfer function, Fuzzy number and Sensitivity in his Fuzzy control system study.
His Control engineering research is multidisciplinary, incorporating perspectives in Actuator and Electronic speed control.
His research on Control system also deals with topics like
- Iterative method which intersects with area such as Optimal control,
- Iterative learning control which is related to area like Trajectory.
He most often published in these fields:
- Control theory (71.99%)
- Fuzzy logic (41.77%)
- Fuzzy control system (37.59%)
What were the highlights of his more recent work (between 2017-2021)?
- Control theory (71.99%)
- Fuzzy logic (41.77%)
- Control theory (23.10%)
In recent papers he was focusing on the following fields of study:
Radu-Emil Precup spends much of his time researching Control theory, Fuzzy logic, Control theory, Control system and Nonlinear system.
His Control theory research incorporates elements of Control, Process and Tensor product.
A large part of his Fuzzy logic studies is devoted to Fuzzy control system.
The Control theory study combines topics in areas such as Linear system and Mobile robot.
In his research on the topic of Control system, Artificial neural network is strongly related with Process control.
His Nonlinear system research focuses on Metaheuristic and how it connects with Adaptive control.
Between 2017 and 2021, his most popular works were:
- Second Order Intelligent Proportional-Integral Fuzzy Control of Twin Rotor Aerodynamic Systems (44 citations)
- Data-driven model reference control of MIMO vertical tank systems with model-free VRFT and Q-Learning. (37 citations)
- Combined Model-Free Adaptive Control with Fuzzy Component by Virtual Reference Feedback Tuning for Tower Crane Systems (33 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Control theory
- Machine learning
The scientist’s investigation covers issues in Control theory, Nonlinear system, Fuzzy logic, Control theory and Fuzzy control system.
His work in the fields of Control theory, such as Control system, Linear system and Sliding mode control, intersects with other areas such as Electromagnetics.
His work in the fields of Nonlinear system, such as Active disturbance rejection control, overlaps with other areas such as Physics.
His research integrates issues of Optimization problem and Adaptive control in his study of Fuzzy logic.
His work deals with themes such as Process control, Mathematical optimization, Robot, Trajectory and Nonholonomic system, which intersect with Control theory.
His Fuzzy control system research integrates issues from Networked control system, Temperature control, Latency and Signal processing.
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