What is he best known for?
The fields of study he is best known for:
- Electrical engineering
- Artificial intelligence
- Control theory
His primary areas of study are Scanning probe microscopy, Feed forward, Control theory, Actuator and Nanotechnology.
His Scanning probe microscopy research is multidisciplinary, relying on both Microscope and Scanning capacitance microscopy.
His research in Feed forward intersects with topics in Image resolution, Repetitive control and Biomedical engineering.
The study incorporates disciplines such as Vibration and Piezoelectricity in addition to Control theory.
His studies in Actuator integrate themes in fields like Fin, Airfoil, Lift-to-drag ratio, Flapping and Mechanical resonance.
His Nanotechnology study combines topics from a wide range of disciplines, such as Acoustics, Piezoelectric actuators and Mechanical engineering, Mechanical design.
His most cited work include:
- Feedback-Linearized Inverse Feedforward for Creep, Hysteresis, and Vibration Compensation in AFM Piezoactuators (304 citations)
- Invited review article: high-speed flexure-guided nanopositioning: mechanical design and control issues. (300 citations)
- A review of feedforward control approaches in nanopositioning for high-speed spm (281 citations)
What are the main themes of his work throughout his whole career to date?
Actuator, Control theory, Feed forward, Tracking error and Robot are his primary areas of study.
His Actuator study combines topics in areas such as Mechanical engineering, Composite material, Simulation and Voltage.
His research on Control theory often connects related topics like Control engineering.
Creep is closely connected to Vibration in his research, which is encompassed under the umbrella topic of Feed forward.
His Tracking error research integrates issues from Iterative learning control, Residual and Robust control.
His study in Repetitive control is interdisciplinary in nature, drawing from both PID controller, Scanning probe microscopy and Motion control.
He most often published in these fields:
- Actuator (36.67%)
- Control theory (36.67%)
- Feed forward (16.67%)
What were the highlights of his more recent work (between 2018-2021)?
- Robot (14.67%)
- Actuator (36.67%)
- Artificial intelligence (8.00%)
In recent papers he was focusing on the following fields of study:
Kam K. Leang mainly focuses on Robot, Actuator, Artificial intelligence, Motion planning and Control theory.
His Robot study incorporates themes from Propulsion, Real-time computing, Nanotechnology and Payload.
The Actuator study combines topics in areas such as Mechanical engineering, Dual stage and Feedforward systems, Feed forward.
The various areas that Kam K. Leang examines in his Mechanical engineering study include Vibration, Bimorph and Wing.
As a part of the same scientific family, Kam K. Leang mostly works in the field of Artificial intelligence, focusing on Computer vision and, on occasion, Bayes estimator.
His research in the fields of Tracking error, Trajectory and Disturbance observer overlaps with other disciplines such as Control equipment and Vehicle control.
Between 2018 and 2021, his most popular works were:
- Coordinated Bayesian-Based Bioinspired Plume Source Term Estimation and Source Seeking for Mobile Robots (9 citations)
- In-Ground-Effect Modeling and Nonlinear-Disturbance Observer for Multirotor Unmanned Aerial Vehicle Control (8 citations)
- 3D-Printing and Machine Learning Control of Soft Ionic Polymer-Metal Composite Actuators. (7 citations)
In his most recent research, the most cited papers focused on:
- Electrical engineering
- Artificial intelligence
- Control theory
Kam K. Leang mainly investigates Robot, Process, Actuator, Real-time computing and Payload.
His studies link Chemical sensor with Robot.
His Actuator research includes elements of Mechanical engineering, Composite number and Machine learning.
His work deals with themes such as Quadcopter and Range, which intersect with Real-time computing.
His study focuses on the intersection of Payload and fields such as Homography with connections in the field of Control theory.
Kam K. Leang integrates Control theory with Motion capture in his study.
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