What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Control theory
- Computer vision
Min Tan mainly investigates Control theory, Artificial neural network, Artificial intelligence, Multi-agent system and Control theory.
His Control theory research incorporates themes from Control engineering and Robot, Robot kinematics, Mobile robot.
His Recurrent neural network study, which is part of a larger body of work in Artificial neural network, is frequently linked to Approximation error, bridging the gap between disciplines.
His research on Artificial intelligence frequently connects to adjacent areas such as Computer vision.
The Consensus research Min Tan does as part of his general Multi-agent system study is frequently linked to other disciplines of science, such as State-transition matrix, therefore creating a link between diverse domains of science.
His Control theory study combines topics from a wide range of disciplines, such as Tracking and Model predictive control.
His most cited work include:
- Decentralized Robust Adaptive Control for the Multiagent System Consensus Problem Using Neural Networks (440 citations)
- Development of a biomimetic robotic fish and its control algorithm (355 citations)
- Neural-Network-Based Adaptive Leader-Following Control for Multiagent Systems With Uncertainties (237 citations)
What are the main themes of his work throughout his whole career to date?
Min Tan focuses on Artificial intelligence, Control theory, Robot, Computer vision and Mobile robot.
His Artificial intelligence study frequently involves adjacent topics like Pattern recognition.
His work carried out in the field of Control theory brings together such families of science as Control engineering and Multi-agent system.
The Robot study which covers Simulation that intersects with Fish fin.
His research investigates the connection between Computer vision and topics such as Welding that intersect with problems in Structured light.
His Mobile robot research includes themes of Biomimetics, Motion planning and Motion control.
He most often published in these fields:
- Artificial intelligence (36.01%)
- Control theory (31.89%)
- Robot (29.22%)
What were the highlights of his more recent work (between 2017-2021)?
- Robot (29.22%)
- Artificial intelligence (36.01%)
- Control theory (31.89%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Robot, Artificial intelligence, Control theory, Computer vision and Control theory.
Min Tan interconnects Motion and Human–computer interaction in the investigation of issues within Robot.
His Artificial intelligence study combines topics in areas such as Transmission line and Pattern recognition.
Min Tan integrates several fields in his works, including Control theory and Pitch angle.
His work carried out in the field of Control theory brings together such families of science as Control system and Point.
His Robustness research is multidisciplinary, incorporating elements of Artificial neural network and Structured light.
Between 2017 and 2021, his most popular works were:
- A Neural-Network-Based Controller for Piezoelectric-Actuated Stick–Slip Devices (48 citations)
- Intracellular manipulation and measurement with multipole magnetic tweezers (34 citations)
- Vision-based autonomous navigation approach for unmanned aerial vehicle transmission-line inspection: (26 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Mechanical engineering
Min Tan spends much of his time researching Artificial intelligence, Control theory, Control theory, Computer vision and Control engineering.
Min Tan combines subjects such as Task and Pattern recognition with his study of Artificial intelligence.
His Control theory research incorporates themes from Robot and Robot end effector.
The various areas that he examines in his Control theory study include Fin, Convergence, Noise, Fuzzy logic and Nonlinear system.
His Monocular vision study in the realm of Computer vision connects with subjects such as Transmission tower.
His Control engineering research incorporates elements of Manipulator, Compensation and Motion planning.
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