What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Computer vision
The scientist’s investigation covers issues in Control theory, Artificial intelligence, Fuzzy control system, Servomechanism and Fuzzy logic.
The study incorporates disciplines such as Optimization problem and Angular displacement in addition to Control theory.
His studies deal with areas such as Grid, Computer vision and Pattern recognition as well as Artificial intelligence.
His Fuzzy control system study is related to the wider topic of Control engineering.
His Servomechanism research is multidisciplinary, relying on both Iterative method, PID controller, Adaptive control and Sensitivity.
His Fuzzy logic research incorporates elements of Stability and Lyapunov function.
His most cited work include:
- Real-time Vision-based Hand Gesture Recognition Using Haar-like Features (277 citations)
- Behavior-based neuro-fuzzy controller for mobile robot navigation (154 citations)
- Sensor-based information appliances (150 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Artificial intelligence, Control theory, Computer vision, Fuzzy logic and Fuzzy control system.
Much of his study explores Artificial intelligence relationship to Pattern recognition.
His Control theory research includes elements of Control engineering and Optimization problem.
The Optimization problem study combines topics in areas such as Simulated annealing, Particle swarm optimization, Search algorithm and Sensitivity.
His Computer vision study often links to related topics such as Virtual reality.
His biological study spans a wide range of topics, including Stability and Lyapunov function.
He most often published in these fields:
- Artificial intelligence (29.64%)
- Control theory (27.58%)
- Computer vision (20.64%)
What were the highlights of his more recent work (between 2016-2021)?
- Control theory (27.58%)
- Fuzzy logic (17.64%)
- Artificial intelligence (29.64%)
In recent papers he was focusing on the following fields of study:
Emil M. Petriu focuses on Control theory, Fuzzy logic, Artificial intelligence, Fuzzy control system and Nonlinear system.
His work on Control system, Control theory, Servomechanism and Active disturbance rejection control is typically connected to Process control as part of general Control theory study, connecting several disciplines of science.
His Fuzzy logic research is multidisciplinary, incorporating perspectives in Linearization, Motion planning, Control and Optimization problem, Mathematical optimization.
His Artificial intelligence research includes themes of Machine learning and Computer vision.
Emil M. Petriu has included themes like Stability, Risk analysis and Component in his Fuzzy control system study.
His studies in Nonlinear system integrate themes in fields like Aerodynamics and Rotor.
Between 2016 and 2021, his most popular works were:
- Grey Wolf Optimizer Algorithm-Based Tuning of Fuzzy Control Systems With Reduced Parametric Sensitivity (127 citations)
- Model-free sliding mode control of nonlinear systems (71 citations)
- An Easily Understandable Grey Wolf Optimizer and Its Application to Fuzzy Controller Tuning (31 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Electrical engineering
Emil M. Petriu mostly deals with Control theory, Fuzzy logic, Fuzzy control system, Debris and Control system.
His Control theory study combines topics from a wide range of disciplines, such as Position control and Mathematical analysis.
The various areas that Emil M. Petriu examines in his Fuzzy logic study include Algorithm, Optimization problem, Control theory and Nonlinear system.
His Optimization problem research focuses on Servomechanism and how it connects with Sensitivity.
He interconnects Signal processing, Computer vision and Networked control system in the investigation of issues within Fuzzy control system.
His work investigates the relationship between Control system and topics such as Metaheuristic that intersect with problems in Control engineering, Angular velocity, Computation and PID controller.
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.
