What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Mechanical engineering
- Control theory
His main research concerns Control theory, Machining, Mathematical analysis, Mathematical optimization and Nonlinear system.
The various areas that Han Ding examines in his Control theory study include Control engineering and Motion control.
The Machining study combines topics in areas such as Calibration and Artifact.
His Mathematical analysis study combines topics in areas such as Rolling-element bearing, Bearing, Condition monitoring and Statistics, Kurtosis.
His research in Mathematical optimization intersects with topics in Topology optimization, Sensitivity, Thermal conduction, Algorithm and Topology.
The concepts of his Nonlinear system study are interwoven with issues in Partial differential equation and Robustness.
His most cited work include:
- A full-discretization method for prediction of milling stability (309 citations)
- Modeling and Control of Piezo-Actuated Nanopositioning Stages: A Survey (277 citations)
- Tool wear characteristics in machining of nickel-based superalloys (261 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Control theory, Machining, Algorithm, Mechanical engineering and Control engineering.
Control theory is frequently linked to Motion control in his study.
His study looks at the intersection of Machining and topics like Vibration with Mechanics.
His Algorithm research incorporates elements of Curvature, Mathematical optimization and Interpolation.
His work carried out in the field of Control theory brings together such families of science as Compensation and Linear motor.
His studies deal with areas such as Discretization, Numerical integration, Mathematical analysis and Applied mathematics as well as Floquet theory.
He most often published in these fields:
- Control theory (28.21%)
- Machining (26.01%)
- Algorithm (12.45%)
What were the highlights of his more recent work (between 2018-2021)?
- Machining (26.01%)
- Artificial intelligence (8.79%)
- Control theory (28.21%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Machining, Artificial intelligence, Control theory, Robot and Algorithm.
His Machining research is multidisciplinary, incorporating elements of Industrial robot, Particle swarm optimization, Chamfer and Machine tool.
His work deals with themes such as Machine learning, Computer vision and Pattern recognition, which intersect with Artificial intelligence.
His Control theory research includes elements of Coupling and Robot end effector.
He interconnects Acoustics, Grinding, Polishing, Position and Point in the investigation of issues within Robot.
Han Ding has researched Algorithm in several fields, including Smoothing, Orientation, Curvature and Chord.
Between 2018 and 2021, his most popular works were:
- Contact force control and vibration suppression in robotic polishing with a smart end effector (29 citations)
- Mobile-robotic machining for large complex components: A review study (20 citations)
- Robotic grinding of a blisk with two degrees of freedom contact force control (17 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Mechanical engineering
- Control theory
Han Ding mostly deals with Machining, Control theory, Industrial robot, Algorithm and Parallelogram.
His Machining research includes themes of Convergence, Rate of convergence and Deformation.
His Control theory research incorporates themes from Piezoelectricity, Mechatronics and Coupling.
His study in Industrial robot is interdisciplinary in nature, drawing from both Control engineering, Robotic arm and Mobile robot.
He has included themes like Tracking, Coordinate system, Interpolation, Smoothness and Line in his Algorithm study.
His Parallelogram study integrates concerns from other disciplines, such as Calibration, Chain, Open-loop controller and Linearization.
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